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AI Engineer 4\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 ((AI Foundations, LLM Core and Agentic AI)\n \n \n Overview: \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (MLX, Agentic AI, Gen AI platform Services)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n \n Team Description: \n \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n \n What You’ll Do: \n \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment \n • \n Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift \n • \n Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines \n • \n Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met \n • \n Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation \n\n \n \n The Ideal Candidate: \n \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n \n Basic Qualifications: \n \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies \n • \n At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n \n Preferred Qualifications: \n \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale \n • \n Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules \n • \n Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (AI Foundations, LLM Core and Agentic AI)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment \n • \n Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift \n • \n Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines \n • \n Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met \n • \n Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies \n • \n At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale \n • \n Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules \n • \n Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (AI Foundations, VLM Customization)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 5\n \n \n Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. \n \n What You’ll Do: \n\n • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:\n, • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams\n, • Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale\n, • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment\n, • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code\n, • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 6 years of experience programming with Python, Java, Golang, or C++\n, • At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data\n, • At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 5+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans\n, • 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)\n, • 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models\n, • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents\n, • Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5\n \n New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5\n \n Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5\n \n Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Applied Researcher 5 (AI Foundations - LLM, Optimization and Finetuning)\n \n \n Overview: \n At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.\n, • Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data.\n, • Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.\n, • Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.\n, • Flex your interpersonal skills to translate the complexity of your work into tangible business goals.\n, • Lead cross-functional research threads that bridge prototype model development and deployment with ML engineering partners, ensuring scientific insights translate to production impact\n\n \n The Ideal Candidate: \n\n • You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers\n, • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them\n, • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea\n, • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond\n, • Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms\n, • Has a deep understanding of the foundations of AI methodologies\n, • Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF.\n, • An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes\n, • Experience in delivering libraries, platform level code or solution level code to existing products\n, • A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects\n, • Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects\n\n \n Basic Qualifications: \n\n • Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research\n\n \n Preferred Qualifications: \n\n • PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fieldsOverview:\n\n\n, • LLM\n \n, • PhD focus on NLP or Masters with 5 years of industrial NLP research experience\n, • Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization)\n, • Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) \n, • Publications in deep learning theory \n, • Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR\n \n\n\n, • Optimization (Training & Inference)\n \n, • PhD focused on topics related to optimizing training of very large deep learning models \n, • Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression \n, • Experience optimizing training for a 10B+ model \n, • Deep knowledge of deep learning algorithmic and/or optimizer design \n, • Experience with compiler design\n \n, • Finetuning\n \n, • PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) \n, • Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance\n, • Experience deploying a fine-tuned large language model\n \n\n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $262,500 - $299,600 for Applied Researcher 5\n \n McLean, VA: $262,500 - $299,600 for Applied Researcher 5\n \n New York, NY: $286,400 - $326,800 for Applied Researcher 5\n \n San Jose, CA: $286,400 - $326,800 for Applied Researcher 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (Vision model (VLM) customization experience)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Applied Researcher 5 (AI Foundations, LLM Core and Agentic AI)\n \n \n At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. \n • \n Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data. \n • \n Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. \n • \n Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. \n • \n Flex your interpersonal skills to translate the complexity of your work into tangible business goals. \n • \n Lead cross-functional research threads that bridge prototype model development and deployment with ML engineering partners, ensuring scientific insights translate to production impact \n\n \n The Ideal Candidate: \n\n • \n You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers \n • \n Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them \n • \n Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea \n • \n A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond \n • \n Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms \n • \n Has a deep understanding of the foundations of AI methodologies \n • \n Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. \n • \n An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes \n • \n Experience in delivering libraries, platform level code or solution level code to existing products \n • \n A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects \n • \n Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects \n\n \n Basic Qualifications: \n\n • \n Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research \n\n \n Preferred Qualifications: \n\n • \n PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields \n • \n LLM \n \n • \n PhD focus on NLP or Masters with 5 years of industrial NLP research experience \n • \n Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) \n • \n Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) \n • \n Publications in deep learning theory \n • \n Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR \n \n • \n Optimization (Training & Inference) \n \n • \n PhD focused on topics related to optimizing training of very large deep learning models \n • \n Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression \n • \n Experience optimizing training for a 10B+ model \n • \n Deep knowledge of deep learning algorithmic and/or optimizer design \n • \n Experience with compiler design \n \n • \n Finetuning \n \n • \n PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) \n • \n Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance \n • \n Experience deploying a fine-tuned large language model \n \n • \n Data Preparation \n \n • \n Publications studying tokenization, data quality, dataset curation, or labeling \n • \n Contribution to a major open source corpus \n • \n Contribution to open source libraries for data quality, dataset curation, or labeling \n \n • \n Proven ability to design and lead small-scale research initiatives, guiding junior researchers or engineers through experimental design and evaluation \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $262,500 - $299,600 for Applied Researcher 5\n \n McLean, VA: $262,500 - $299,600 for Applied Researcher 5\n \n New York, NY: $286,400 - $326,800 for Applied Researcher 5\n \n San Francisco, CA: $286,400 - $326,800 for Applied Researcher 5\n \n San Jose, CA: $286,400 - $326,800 for Applied Researcher 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (Gen AI Platform Services)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (FM Hosting, LLM Inference)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 5 (IC)\n \n \n Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. \n \n What You’ll Do: \n\n • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:\n, • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams\n, • Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale\n, • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment\n, • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code\n, • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 6 years of experience programming with Python, Java, Golang, or C++\n, • At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data\n, • At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 5+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans\n, • 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)\n, • 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models\n, • 4+ years of on-the-job experience with an industry recognized ML framework such as Dask or XGboost.\n, • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents\n, • Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5\n \n New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5\n \n Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Manager, Machine Learning Engineer\n \n \n Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. \n \n What You’ll Do: \n\n • \n The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: \n • \n Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams \n • \n Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale \n • \n Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) \n • \n Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n • \n Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications \n • \n Retrain, maintain, and monitor models in production \n • \n Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. \n • \n Construct optimized data pipelines to feed ML models \n • \n Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n • \n Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI \n • \n Use programming languages like Python, Scala, or Java \n\n \n Basic Qualifications: \n\n • \n Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) \n • \n At least 6 years of experience programming with Python, Java, Golang, or C++ \n • \n At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) \n • \n At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data \n • \n At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems \n\n \n Preferred Qualifications: \n\n • \n Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field \n • \n 5+ years of experience optimizing ML algorithms, configurations, and infrastructure \n • \n 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n • \n 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans \n • \n 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) \n • \n 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models \n • \n ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents \n • \n Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5\n \n McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5\n \n New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Applied Researcher 5\n \n \n At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. \n • \n Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data. \n • \n Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. \n • \n Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. \n • \n Flex your interpersonal skills to translate the complexity of your work into tangible business goals. \n • \n Lead cross-functional research threads that bridge prototype model development and deployment with ML engineering partners, ensuring scientific insights translate to production impact \n\n \n The Ideal Candidate: \n\n • \n You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers \n • \n Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them \n • \n Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea \n • \n A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond \n • \n Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms \n • \n Has a deep understanding of the foundations of AI methodologies \n • \n Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. \n • \n An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes \n • \n Experience in delivering libraries, platform level code or solution level code to existing products \n • \n A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects \n • \n Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects \n\n \n Basic Qualifications: \n\n • \n Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research \n\n \n Preferred Qualifications: \n\n • \n PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields \n • \n LLM \n \n • \n PhD focus on NLP or Masters with 5 years of industrial NLP research experience \n • \n Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) \n • \n Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) \n • \n Publications in deep learning theory \n • \n Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR \n \n • \n Optimization (Training & Inference) \n \n • \n PhD focused on topics related to optimizing training of very large deep learning models \n • \n Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression \n • \n Experience optimizing training for a 10B+ model \n • \n Deep knowledge of deep learning algorithmic and/or optimizer design \n • \n Experience with compiler design \n \n • \n Finetuning \n \n • \n PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) \n • \n Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance \n • \n Experience deploying a fine-tuned large language model \n \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $262,500 - $299,600 for Applied Researcher 5\n \n McLean, VA: $262,500 - $299,600 for Applied Researcher 5\n \n New York, NY: $286,400 - $326,800 for Applied Researcher 5\n \n San Jose, CA: $286,400 - $326,800 for Applied Researcher 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Staff AI Engineer (Remote Eligible)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale\n, • Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide\n, • Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture\n, • Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One’s AI technical leadership\n\n \n Capital One is open to hiring a Remote Employee for this opportunity. \n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies\n, • At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy\n, • 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership\n, • Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance\n, • Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams\n, • Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer\n \n Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer\n \n McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer\n \n New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 4 - Intelligent Foundations and Experiences (IFX)\n \n \n Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. \n \n What You’ll Do: \n\n • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:\n, • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams\n, • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n, • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n, • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 4 years of experience programming with Python, Java, Golang, or C++\n, • At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data\n, • At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 3+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans.\n, • 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)\n, • 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.\n, • 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation \n, • Authored/co-authored a paper on a ML technique, model, or proof of concept\n\n \n At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4\n \n New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Manager, AI Engineer (IFX)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One \n • \n Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One \n • \n Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI \n • \n Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts \n • \n Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems \n • \n Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 1 year of people leadership experience \n\n \n Preferred Qualifications: \n\n • \n 3 years of experience managing and leading an engineering team \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery \n • \n Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance \n • \n Track record mentoring engineers/scientists to productize prototypes and meet production SLOs \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer\n \n McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer\n \n New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (AI Foundations: LLM Customization, Finetuning, Reinforcement Learning)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Applied Researcher 4 (AI Foundations, LLM Customization and Finetuning)\n \n \n At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.\n, • Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data.\n, • Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.\n, • Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.\n, • Flex your interpersonal skills to translate the complexity of your work into tangible business goals.\n, • Collaborate with senior researchers to prepare internal tech reports or conference submissions summarizing novel methods or findings\n\n \n The Ideal Candidate: \n\n • You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers\n, • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them\n, • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea\n, • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond\n, • Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms\n, • Has a deep understanding of the foundations of AI methodologies\n, • Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF\n, • An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes\n, • Experience in delivering libraries, platform level code or solution level code to existing products\n, • A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects\n, • Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects\n\n \n Basic Qualifications: \n\n • Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research\n\n \n Preferred Qualifications: \n\n • PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields\n, • LLM\n \n, • PhD focus on NLP or Masters with 5 years of industrial NLP research experience\n, • Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization)\n, • Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) \n, • Publications in deep learning theory \n, • Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR\n \n, • Finetuning\n \n, • PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) \n, • Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance\n, • Experience deploying a fine-tuned large language model \n \n, • Data Preparation\n \n, • Publications studying tokenization, data quality, dataset curation, or labeling \n, • Contribution to a major open source corpus \n, • Contribution to open source libraries for data quality, dataset curation, or labeling\n \n, • Demonstrated ability to reproduce and extend peer-reviewed AI research using modern open-source frameworks\n, • Experience designing controlled experiments and documenting reproducibility results for internal or public research\n\n \n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $218,700 - $249,600 for Applied Researcher 4\n \n McLean, VA: $218,700 - $249,600 for Applied Researcher 4\n \n New York, NY: $238,600 - $272,300 for Applied Researcher 4\n \n San Jose, CA: $238,600 - $272,300 for Applied Researcher 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Staff AI Engineer\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams\n, • Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads\n, • Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design\n, • Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies\n, • At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks\n, • Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency\n, • Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization\n, • Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility \n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n ion. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer\n \n McLean, VA: $269,100 - $307,200 for Staff AI Engineer\n \n New York, NY: $293,600 - $335,100 for Staff AI Engineer\n \n San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer\n \n San Jose, CA: $293,600 - $335,100 for Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (AI Foundations, VLM Customization)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment \n • \n Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift \n • \n Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines \n • \n Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met \n • \n Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies \n • \n At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale \n • \n Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules \n • \n Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Applied Researcher 4\n \n \n At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.\n, • Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data.\n, • Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.\n, • Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.\n, • Flex your interpersonal skills to translate the complexity of your work into tangible business goals.\n, • Collaborate with senior researchers to prepare internal tech reports or conference submissions summarizing novel methods or findings\n\n \n The Ideal Candidate: \n\n • You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers\n, • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them\n, • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea\n, • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond\n, • Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms\n, • Has a deep understanding of the foundations of AI methodologies\n, • Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF\n, • An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes\n, • Experience in delivering libraries, platform level code or solution level code to existing products\n, • A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects\n, • Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects\n\n \n Basic Qualifications: \n\n • Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research\n\n \n Preferred Qualifications \n\n • PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields\n, • LLM\n \n, • PhD focus on NLP or Masters with 5 years of industrial NLP research experience\n, • Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization)\n, • Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) \n, • Publications in deep learning theory \n, • Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR\n \n, • Optimization (Training & Inference)\n \n, • PhD focused on topics related to optimizing training of very large deep learning models \n, • Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression \n, • Experience optimizing training for a 10B+ model \n, • Deep knowledge of deep learning algorithmic and/or optimizer design \n, • Experience with compiler design\n \n, • Finetuning\n \n, • PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) \n, • Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance\n, • Experience deploying a fine-tuned large language model \n \n\n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $218,700 - $249,600 for Applied Researcher 4\n \n McLean, VA: $218,700 - $249,600 for Applied Researcher 4\n \n New York, NY: $238,600 - $272,300 for Applied Researcher 4\n \n San Jose, CA: $238,600 - $272,300 for Applied Researcher 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (MLX, Agentic AI, Gen AI platform Services)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n \n Team Description: \n \n \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n \n \n What You’ll Do: \n \n \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n \n The Ideal Candidate: \n \n \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n \n \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n \n Preferred Qualifications: \n \n \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One \n • \n Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One \n • \n Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI \n • \n Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts \n • \n Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems \n • \n Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 1 year of people leadership experience \n\n \n Preferred Qualifications: \n\n • \n 3 years of experience managing and leading an engineering team \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery \n • \n Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance \n • \n Track record mentoring engineers/scientists to productize prototypes and meet production SLOs \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer\n \n McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer\n \n New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n San Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Staff AI Engineer (Remote Eligible)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams\n, • Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads\n, • Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design\n, • Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown.\n\n \n Capital One is open to hiring a Remote Employee for this opportunity \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies\n, • At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks\n, • Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency\n, • Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization\n, • Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility \n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Remote (Regardless of Location): $244,700 - $279,200 for Staff AI Engineer\n \n Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer\n \n McLean, VA: $269,100 - $307,200 for Staff AI Engineer\n \n New York, NY: $293,600 - $335,100 for Staff AI Engineer\n \n San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer\n \n San Jose, CA: $293,600 - $335,100 for Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 4 (Manager, IC)\n \n \n Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. \n \n What You’ll Do: \n\n • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:\n, • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams\n, • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n, • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n, • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 4 years of experience programming with Python, Java, Golang, or C++\n, • At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data\n, • At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 3+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans.\n, • 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)\n, • 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.\n, • 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation \n, • Authored/co-authored a paper on a ML technique, model, or proof of concept\n\n \n At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Chicago, IL: $179,400 - $204,700 for Machine Learning Engineer 4\n \n New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Applied Researcher 4 (AI Foundations, LLM Core and Agentic AI)\n \n \n At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. \n • \n Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data. \n • \n Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. \n • \n Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. \n • \n Flex your interpersonal skills to translate the complexity of your work into tangible business goals. \n • \n Collaborate with senior researchers to prepare internal tech reports or conference submissions summarizing novel methods or findings \n\n \n The Ideal Candidate: \n\n • \n You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers \n • \n Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them \n • \n Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea \n • \n A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond \n • \n Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms \n • \n Has a deep understanding of the foundations of AI methodologies \n • \n Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF \n • \n An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes \n • \n Experience in delivering libraries, platform level code or solution level code to existing products \n • \n A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects \n • \n Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects \n\n \n Basic Qualifications: \n\n • \n Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research \n\n \n Preferred Qualifications: \n\n • \n PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields \n • \n LLM \n \n • \n PhD focus on NLP or Masters with 5 years of industrial NLP research experience \n • \n Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) \n • \n Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) \n • \n Publications in deep learning theory \n • \n Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR \n \n • \n Optimization (Training & Inference) \n \n • \n PhD focused on topics related to optimizing training of very large deep learning models \n • \n Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression \n • \n Experience optimizing training for a 10B+ model \n • \n Deep knowledge of deep learning algorithmic and/or optimizer design \n • \n Experience with compiler design \n \n • \n Finetuning \n \n • \n PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) \n • \n Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance \n • \n Experience deploying a fine-tuned large language model \n \n • \n Data Preparation \n \n • \n Publications studying tokenization, data quality, dataset curation, or labeling \n • \n Contribution to a major open source corpus \n • \n Contribution to open source libraries for data quality, dataset curation, or labeling \n \n • \n Demonstrated ability to reproduce and extend peer-reviewed AI research using modern open-source frameworks \n • \n Experience designing controlled experiments and documenting reproducibility results for internal or public research \n\n \n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $218,700 - $249,600 for Applied Researcher 4\n \n McLean, VA: $218,700 - $249,600 for Applied Researcher 4\n \n New York, NY: $238,600 - $272,300 for Applied Researcher 4\n \n San Francisco, CA: $238,600 - $272,300 for Applied Researcher 4\n \n San Jose, CA: $238,600 - $272,300 for Applied Researcher 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Applied Researcher 4 (AI Foundations - LLM, Optimization and Finetuning)\n \n \n Overview: \n At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.\n, • Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data.\n, • Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.\n, • Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.\n, • Flex your interpersonal skills to translate the complexity of your work into tangible business goals.\n, • Collaborate with senior researchers to prepare internal tech reports or conference submissions summarizing novel methods or findings\n\n \n The Ideal Candidate: \n\n • You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers\n, • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them\n, • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea\n, • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond\n, • Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms\n, • Has a deep understanding of the foundations of AI methodologies\n, • Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF\n, • An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes\n, • Experience in delivering libraries, platform level code or solution level code to existing products\n, • A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects\n, • Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects\n\n \n Basic Qualifications: \n\n • Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research\n\n \n Preferred Qualifications: \n\n • PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields\n, • LLM\n \n, • PhD focus on NLP or Masters with 5 years of industrial NLP research experience\n, • Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization)\n, • Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) \n, • Publications in deep learning theory \n, • Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR\n \n\n\n, • Optimization (Training & Inference)\n \n, • PhD focused on topics related to optimizing training of very large deep learning models \n, • Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression \n, • Experience optimizing training for a 10B+ model \n, • Deep knowledge of deep learning algorithmic and/or optimizer design \n, • Experience with compiler design\n \n, • Finetuning\n \n, • PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) \n, • Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance\n, • Experience deploying a fine-tuned large language model\n \n\n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $218,700 - $249,600 for Applied Researcher 4\n \n McLean, VA: $218,700 - $249,600 for Applied Researcher 4\n \n New York, NY: $238,600 - $272,300 for Applied Researcher 4\n \n San Jose, CA: $238,600 - $272,300 for Applied Researcher 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (Gen AI Platform Services - Agentic Systems)\n \n \n Overview: \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (GenAI Platform Services, Agentic Platform)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology)\n \n \n Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. \n \n Enterprise Platforms Technology (EPTech) comprises many of Capital One’s most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. \n \n Team: \n The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. \n \n What You’ll Do: \n\n • The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:\n, • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams\n, • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n, • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n, • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 4 years of experience programming with Python, Java, Golang, or C++\n, • At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data\n, • At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 3+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 3+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans.\n, • 3+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting)\n, • 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.\n, • 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation \n, • Authored/co-authored a paper on a ML technique, model, or proof of concept\n\n \n At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). \n \n \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4\n \n New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4\n \n Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4\n \n Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for Machine Learning Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 3 (AI Foundations)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Lead development and benchmarking of multi-turn conversational and tool-using agent workflows, ensuring measurable performance and safety metrics \n • \n Implement scalable pipelines for training, fine-tuning and deploying foundation or domain-specific models across multiple environments \n • \n Collaborate with research and data engineering teams to curate high-quality datasets and improve model evaluation methodologies \n • \n Contribute to governance and security efforts for model traceability, lineage documentation, and version control of deployed AI assets \n • \n Mentor junior AI engineers and advocate for engineering excellence, reproducibility, and responsible experimentation \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 3 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 1 year of experience developing AI and ML algorithms or technologies \n • \n At least 3 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience contributing to development of components of AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 4 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Demonstrated ability to evaluate and optimize LLM performance using quantitative metrics (accuracy, coherence, latency, cost) \n • \n Hands-on experience implementing retrieval-augmented generation (RAG), vector database integrations, and fine-tuning workflows \n • \n Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies to production AI systems \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $161,800 - $184,600 for AI Engineer 3\n \n McLean, VA: $161,800 - $184,600 for AI Engineer 3\n \n New York, NY: $176,500 - $201,400 for AI Engineer 3\n \n San Jose, CA: $176,500 - $201,400 for AI Engineer 3\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Staff AI Engineer - Agentic AI Platform (Remote Eligible)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n Capital One is open to hiring a Remote Employee for this opportunity \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale\n, • Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide\n, • Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture\n, • Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One’s AI technical leadership\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies\n, • At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy\n, • 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership\n, • Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance\n, • Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams\n, • Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer\n \n Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer\n \n McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer\n \n New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (MLX)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Staff AI Engineer role (Remote Eligible)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams\n, • Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads\n, • Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design\n, • Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Capital One is open to hiring a Remote Employee for this opportunity. \n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies\n, • At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 8+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks\n, • Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency\n, • Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization\n, • Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility \n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Remote (Regardless of Location): $244,700 - $279,200 for Staff AI Engineer\n \n Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer\n \n McLean, VA: $269,100 - $307,200 for Staff AI Engineer\n \n New York, NY: $293,600 - $335,100 for Staff AI Engineer\n \n San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer\n \n San Jose, CA: $293,600 - $335,100 for Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Applied Researcher 4 (AI Foundations, Graph and Behavioral Models)\n \n \n At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. \n • \n Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data. \n • \n Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. \n • \n Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. \n • \n Flex your interpersonal skills to translate the complexity of your work into tangible business goals. \n • \n Collaborate with senior researchers to prepare internal tech reports or conference submissions summarizing novel methods or findings \n\n \n The Ideal Candidate: \n\n • \n You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers \n • \n Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them \n • \n Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea \n • \n A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond \n • \n Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms \n • \n Has a deep understanding of the foundations of AI methodologies \n • \n Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF \n • \n An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes \n • \n Experience in delivering libraries, platform level code or solution level code to existing products \n • \n A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects \n • \n Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects \n\n \n Basic Qualifications: \n\n • \n Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research \n\n \n Preferred Qualifications: \n\n • \n PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields \n • \n LLM \n \n • \n PhD focus on NLP or Masters with 5 years of industrial NLP research experience \n • \n Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) \n • \n Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) \n • \n Publications in deep learning theory \n • \n Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR \n \n • \n Behavioral Models \n \n • \n PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) \n • \n Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR \n • \n Worked on scaling graph models to greater than 50m nodes \n • \n Experience with large scale deep learning based recommender systems \n • \n Experience with production real-time and streaming environments \n • \n Contributions to common open source frameworks (pytorch-geometric, DGL) \n • \n Proposed new methods for inference or representation learning on graphs or sequences \n • \n Worked datasets with 100m+ users \n \n • \n Finetuning \n \n • \n PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) \n • \n Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance \n • \n Experience deploying a fine-tuned large language model \n \n • \n Data Preparation \n \n • \n Publications studying tokenization, data quality, dataset curation, or labeling \n • \n Contribution to a major open source corpus \n • \n Contribution to open source libraries for data quality, dataset curation, or labeling \n \n • \n Demonstrated ability to reproduce and extend peer-reviewed AI research using modern open-source frameworks \n • \n Experience designing controlled experiments and documenting reproducibility results for internal or public research \n\n \n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $218,700 - $249,600 for Applied Researcher 4\n \n McLean, VA: $218,700 - $249,600 for Applied Researcher 4\n \n New York, NY: $238,600 - $272,300 for Applied Researcher 4\n \n San Jose, CA: $238,600 - $272,300 for Applied Researcher 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (GenAI Platform, Agentic Infrastructure)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

JOB SUMMARY: Andy Frain Services is looking for a highly motivated individual that is multi-task oriented to assist in managing a Security contract. Manages the accountability of all Supervisors and staff for given accounts. Has full responsibility for performance, service and budget of assigned contracts. Manages a safe environment for all employees, vendors, and personnel. Support all areas in their security needs and be an integral part of the facility needs. Establish working relationships with local police and fire departments, as well as with facility reports and others. Demonstrates and abides by Andy Frain Services Core Values and the operating principles set forth, while maintaining 100% compliance w/all staff training. Managers must possess and maintain a professional image and must demonstrate strong leadership skills. RESPONSIBILITIES/DUTIES: • The functions listed describe the business purpose of this job. Specific duties or tasks may vary and be documented separately. The employee might not be required to perform all functions listed. Additional duties may be assigned, and functions may be modified, according to business necessity., • Employees are held accountable for successful job performance. Job performance standards may be documented separately, and may include functions, objectives, duties or tasks not specifically listed herein., • In performing functions, duties or tasks, employees are required to know and follow safe work practices, and to be aware of company policies and procedures related to job safety, including safety rules and regulations. Employees are required to notify superiors upon becoming aware of unsafe working conditions., • All functions, duties or tasks are to be carried out in an honest, ethical and professional manner, and to be performed in conformance with applicable company policies and procedures. In the event of uncertainty or lack of knowledge of company policies and procedures, employees are required to request clarification or explanations from superiors or authorized company representatives., • The delivery of quality service and positive interaction with our customers is critical to the completion of all the tasks within this job description. The ability to greet all visitors, vendors, and employees; while continuously maintaining the standards of excellence in presentation and professionalism. This is also a requirement of your staff., • Provide lead direction at assigned client site(s); to enforce security/safety programs and ensure that post orders are followed, that established rounds are completed, and that adequate reports and logs are filed daily and weekly., • Develop and implement security procedures and compliance with facility policies and procedures and applicable stated and federal laws. Maintain a working knowledge of all emergency policies, procedures and regulations; respond immediately to emergency alarms or calls for help, determine course of action, notify appropriate authorities and assist as needed., • Knowledge of life safety systems, fire panels, CCTV system computers. Staff is to ensure the continuous and safe operation of all elevators and access doors is critical. Maintain contact with authorized personnel/contractors who are responsible for maintenance and upkeep of said devices., • Equipment operation will include use of portable radios, telephones, copy and fax machines, computers and tools. This includes making daily inspection of all vehicles assigned to job site and noting any damages so that repairs can be handled immediately thus maximizing use of the units at all times., • May counsel and discipline personnel as appropriate; seeks advice from company management or designated representatives as appropriate; meets personally with employees and documents counseling and disciplinary actions., • Assists in the training of Security Officers and Shift Lead Officers, and review of post orders ensuring that Guards have competent knowledge of assignments., • Communicate with Operations manager daily and weekly regarding account performance and Security Officer performance. Communicate daily and weekly regarding security and safety issues/changes that need to be implemented., • Assists in the submission of payroll and personnel information to the company as designated., • In conjunction with company management or designated company representatives acts to ensure adequate security coverage of all posts., • Inspects posts as scheduled and meets with Staff to outline tasks and responsibilities. Ensure that Staff sign in and out for their scheduled shifts accurately for every shift., • Meets with client representatives as scheduled or as needed to provide assurance that all security requirements are being met and to provide quality customer service., • Carry out other duties as assigned by Managing Director. EDUCATION EXPERIENCE: • High School Diploma and/or equivalent; Associates Degree., • Must be willing to submit to a background investigation; any offer of employment is conditioned upon the successful completion of a background investigation., • Bachelor’s degree in related field or equivalent combination of education and experience., • Minimum 2 years prior experience in loss prevention, life safety, CCTV systems and access computer system., • One year (1 yr.) of which must be in the capacity of a management position within the Security Industry., • Valid Driver’s License, • Complete all licensing requirements as mandated by the State., • CPR and First Aid Certification a plus., • Additional qualifications may be specified and receive preference, depending upon the nature of the position. SKILLS AND ABILITIES: • Have complete knowledge of facility layout and operational requirements outlined by the customer., • Implement all AFS and customer safety and security procedures as required., • Design staffing and security plans for operations., • Identify recruiting sources and maintain relationships with all sources., • Recruit and hire all personnel for staffing plan., • Train and certify all security and operation staff on an ongoing basis., • Build teams that are highly motivated to exceed customer expectations., • Effectively manage the administrative duties for accurate and timely payroll and reports., • Create processes that will improve the overall safety and security of the facility plan., • Develop a training program that builds employee performance., • Implement a safety program in compliance with company standards., • Create post orders and internal policy and procedures material for staff compliance., • Regularly meet with the customer and city representatives to assess our performance and develop “best practices” or strategies to improve services., • Maintain current records on all licensed security officers in compliance with city and state regulations. • Create employee recognition programs that motivate employee performance., • Identify local organizations to support community services., • Maintain fiscal responsibility for the profitability of the account., • Achieve management objective in growing business through network opportunities., • Develop and implement sales strategy to grow business., • Must be able to meet and continue to meet any applicable state, county and municipal licensing requirements for Security Officers., • Must be able to meet and continue to meet requirements for specific skills, certifications or authorizations specified for the assigned site., • Knowledge of security operations and procedures., • Knowledge of management practices and procedures., • Ability to provide positive direction and motivate performance., • Understanding of a variety of security and safety devices and controls., • Ability to track and maintain schedule assignments., • Ability to be an effective team member., • Ability to maintain professional composure when dealing with unusual circumstances., • Ability to adapt to various sites and changes in post procedures., • Ability to adapt to changes in the external environment and organization., • Excellent organizational skills., • Strong customer service and results orientation., • Strong interpersonal skills, with the ability to interact effectively with clients, at various social levels and across diverse cultures. WORKING CONDITIONS (Physical/Mental Demands) With or without reasonable accommodation, requires the physical and mental capacity to perform effectively all essential functions. In addition to other demands, the demands of the job include: • Maintaining composure in dealing with authorities, executives, clients, staff and the public, occasionally under conditions of urgency and in pressure situations., • May be exposed to stressful situations, such as challenging individuals who are in or approaching an unauthorized area., • Must undergo and meet company standards for background and reference checks, controlled substance testing, and behavioral selection survey, in addition to any mandatory licensing requirements and site-specific requirements., • Directing staff in a positive manner., • May be required to work overtime without advance notice., • Required ability to handle multiple tasks concurrently., • Keyboarding, basic computer usage and operating controls., • Seeing, hearing, speaking, and writing clearly in order to communicate with employees and clients, observe and report incidents, and direct others., • Frequent sitting, standing and walking, which may be required for long periods of time, and may involve climbing stairs and walking up inclines and on uneven terrain., • Occasional reaching with hands and arms, stooping, kneeling, crouching and crawling., • Frequent lifting and/or moving up to 10 pounds, occasional lifting and/or moving up to 25 pounds, and additional lifting and/or moving ability as might be required for the assigned site., • Close vision, distance vision, and ability to adjust focus., • May be required to use vehicle for the performance of duties., • On occasion may be required to perform stressful and physical activity., • Normal vision or corrected by use of glasses and/or contacts for normal reading and viewing abilities., • Depending upon assignment may be exposed to inclement weather or be required to work in environments or under conditions that require the use of protective gear and devices and/or awareness of personal safety and safety of others., • May be exposed to or required to handle sensitive and confidential information. Salary/Benefits: Competitive Salary, Vacation/PTO, Medical/Dental/Vision, 401K. This description portrays in general terms the type and level(s) of work performed and is not intended to be all-inclusive, nor the specific duties of any one incumbent. Andy Frain Services reserves the right to modify, supplement, delete or augment the duties and responsibilities specified in the position description, in the Company’s sole and absolute discretion. Duties other than those expressly specified may be assigned from time to time.

JOB SUMMARY: Supervision of all employees assigned to the Security department, with full responsibility for performance management of said staff. Manage and oversee all assigned areas in order to maintain a safe environment for all employees, vendors, and personnel. Support all areas in their security needs and be an integral part of the facility needs. Establish working relationships with local police and fire departments, as well as, with facility reports and others. Demonstrates and abides by Andy Frain Services Core Values and the operating principles set forth, while maintaining 100% compliance w/all staff training. Observes and reports activities and incidents providing for the security and safety of client property and personnel. Supervisors must possess and maintain a professional image and must demonstrate strong leadership skills. ESSENTIAL FUNCTIONS The functions listed describe the business purpose of this job. Specific duties or tasks may vary and be documented separately. The employee might not be required to perform all functions listed. Additional duties may be assigned, and functions may be modified, according to business necessity. • Employees are held accountable for successful job performance. Job performance standards may be documented separately, and may include functions, objectives, duties or tasks not specifically listed herein., • In performing functions, duties or tasks, employees are required to know and follow safe work practices, and to be aware of company policies and procedures related to job safety, including safety rules and regulations. Employees are required to notify superiors upon becoming aware of unsafe working conditions., • All functions, duties or tasks are to be carried out in an honest, ethical and professional manner, and to be performed in conformance with applicable company policies and procedures. In the event of uncertainty or lack of knowledge of company policies and procedures, employees are required to request clarification or explanations from superiors or authorized company representatives., • Performs the duties of a Security Officer in accord with post orders and company policy., • The delivery of quality service and positive interaction with our customers is critical to the completion of all the tasks within this job description. The ability to greet all visitors, vendors, and employees; while continuously maintaining the standards of excellence in presentation and professionalism. This is also a requirement of your staff., • Provide lead direction at assigned client site(s); to enforce security/safety programs and ensure that post orders are followed, that established rounds are completed, and that adequate reports and logs are filed daily and weekly., • Develop and implement security procedures and compliance with facility policies and procedures and applicable stated and federal laws. Maintain a working knowledge of all emergency policies, procedures and regulations; respond immediately to emergency alarms or calls for help, determine course of action, notify appropriate authorities and assist as needed., • Knowledge of life safety systems, fire panels, CCTV system computers, the Micro-Lite System. Staff is to ensure the continuous and safe operation of all elevators and access doors is critical. Maintain contact with authorized personnel/contractors who are responsible for maintenance and upkeep of said devices., • Equipment operation will include use of portable radios, telephones, copy and fax machines, computers and tools. This includes making daily inspection of all vehicles assigned to job site and noting any damages so that repairs can be handled immediately thus maximizing use of the units at all times., • May counsel and discipline personnel as appropriate; seeks advice from company management or designated representatives as appropriate; meets personally with employees and documents counseling and disciplinary actions., • Assists in the training of Security Officers and Shift Lead Officers, and review of post orders ensuring that Guards have competent knowledge of assignments., • Communicate with Operations manager daily and weekly regarding account performance and Security Guard performance. Communicate daily and weekly regarding security and safety issues/changes that need to be implemented., • Assists in the submission of payroll and personnel information to the company as designated., • In conjunction with company management or designated company representatives acts to ensure adequate security coverage of all posts., • Inspects posts as scheduled and meets with Staff to outline tasks and responsibilities. Ensure that Staff sign in and out for their scheduled shifts accurately for every shift., • Meets with client representatives as scheduled or as needed to provide assurance that all security requirements are being met and to provide quality customer service., • Carry out other duties as assigned by Director of Security and Operations Manager. MINIMUM QUALIFICATIONS AT ENTRY Additional qualifications may be specified and receive preference, depending upon the nature of the position. Education/Experience: • High School Diploma and/or equivalent; Required, • Minimum 2 years prior experience in loss prevention, life safety, CCTV systems and access computer system, one year of which must be in the capacity of a supervisory position within the Security Industry., • Must be willing to submit to a background investigation; any offer of employment is conditioned upon the successful completion of a background investigation., • State Guard License is required., • CPR and First Aid Certification a plus. Competencies (as demonstrated through experience, training, and/or testing): • Must be able to meet and continue to meet any applicable state, county and municipal licensing requirements for Security Officers., • Must be able to meet and continue to meet requirements for specific skills, certifications or authorizations specified for the assigned site., • Knowledge of security operations and procedures., • Knowledge of supervisory practices and procedures., • Ability to provide positive direction and motivate performance., • Understanding of a variety of security and safety devices and controls., • Ability to learn quickly and carry out instructions furnished in written, oral, or diagrammatic form., • Ability to track and maintain schedule assignments., • Ability to be an effective team member., • Ability to maintain professional composure when dealing with unusual circumstances., • Courteous telephone manner., • Ability to adapt to various sites and changes in post procedures., • Ability to adapt to changes in the external environment and organization., • Ability to write routine correspondence, including logs and reports., • Good organizational skills., • Strong customer service and results orientation., • Strong interpersonal skills, with the ability to interact effectively with clients, at various social levels and across diverse cultures. WORKING CONDITIONS (Physical/Mental Demands) With or without reasonable accommodation, requires the physical and mental capacity to perform effectively all essential functions. In addition to other demands, the demands of the job include: • Maintaining composure in dealing with authorities, executives, clients, staff and the public, occasionally under conditions of urgency and in pressure situations., • May be exposed to stressful situations, such as challenging individuals who are in or approaching an unauthorized area., • Must undergo and meet company standards for background and reference checks, controlled substance testing, and behavioral selection survey, in addition to any mandatory licensing requirements and site-specific requirements., • Directing staff in a positive manner., • May be required to work overtime without advance notice., • Required ability to handle multiple tasks concurrently., • Keyboarding, basic computer usage and operating controls., • Seeing, hearing, speaking, and writing clearly in order to communicate with employees and clients, observe and report incidents, and direct others., • Frequent sitting, standing and walking, which may be required for long periods of time, and may involve climbing stairs and walking up inclines and on uneven terrain., • Occasional reaching with hands and arms, stooping, kneeling, crouching and crawling., • Frequent lifting and/or moving up to 10 pounds, occasional lifting and/or moving up to 25 pounds, and additional lifting and/or moving ability as might be required for the assigned site., • Close vision, distance vision, and ability to adjust focus., • May be required to use vehicle for the performance of duties., • On occasion may be required to perform stressful and physical activity., • Normal vision or corrected by use of glasses and/or contacts for normal reading and viewing abilities., • Depending upon assignment may be exposed to inclement weather or be required to work in environments or under conditions that require the use of protective gear and devices and/or awareness of personal safety and safety of others., • May be exposed to or required to handle sensitive and confidential information. Compensation/Benefits: Competitive Pay, Vacation/PTO, Medical/Dental/Vision, 401K. This description portrays in general terms the type and level(s) of work performed and is not intended to be all-inclusive, nor the specific duties of any one incumbent. Andy Frain Services reserves the right to modify, supplement, delete or augment the duties and responsibilities specified in the position description, in the Company’s sole and absolute discretion. Duties other than those expressly specified may be assigned from time to time.

Sr. Staff Applied Researcher At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. This is an individual contributor (IC) role driving strategic direction through collaboration with Applied Science, Engineering and Product leaders across Capital One. As a well-respected IC leader, you will guide and mentor a team of applied scientists and their managers without being a direct people leader. You will be expected to be an external leader representing Capital One in the research community, collaborating with prominent faculty members in the relevant AI research community. What You’ll Do: • Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money., • Leverage a broad stack of technologies — Pytorch, AWS Ultraclusters, Huggingface, Lightning, and more — to reveal the insights hidden within huge volumes of numeric and textual data., • Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation., • Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences., • Flex your interpersonal skills to translate the complexity of your work into tangible business goals., • Define and evolve the company’s long-term research agenda - identifying emergent scientific opportunities and steering foundational investments in AI innovation The Ideal Candidate: • You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers, • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them, • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea, • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond, • Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms, • Has a deep understanding of the foundations of AI methodologies, • Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF, • An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes, • Experience in delivering libraries, platform level code or solution level code to existing products, • A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects, • Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects Basic Qualifications: • PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 6 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 8 years of experience in Applied Research Preferred Qualifications: • PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields, • LLM, • PhD focus on NLP or Masters with 10 years of industrial NLP research experience, • Core contributor to team that has trained a large language model from scratch (10B + parameters, 500B+ tokens), • Numerous publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization), • Has worked on an LLM (open source or commercial) that is currently available for use, • Demonstrated ability to guide the technical direction of a large-scale model training team, • Experience working with 500+ node clusters of GPUs Has worked on LLM scaled to 70B parameters and 1T+ tokens, • Experience with common training optimization frameworks (deep speed, nemo), • Behavioral Models, • PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series), • Member of technical leadership for model deployment for a very large user behavior model, • Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR, • Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems, • Experience with production real-time and streaming environments, • Contributions to common open source frameworks (pytorch-geometric, DGL), • Proposed new methods for inference or representation learning on graphs or sequences, • Worked datasets with 100m+ users, • Optimization (Training & Inference), • PhD focused on topics related to optimizing training of very large language models, • 5+ years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression, • Finetuning, • PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning), • Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance, • Experience deploying a fine-tuned large language model, • Data Preparation, • Numerous Publications studying tokenization, data quality, dataset curation, or labeling, • Leading contributions to one or more large open source corpus (1 Trillion + tokens), • Core contributor to open source libraries for data quality, dataset curation, or labeling, • Recognized authority in AI or ML research with demonstrated influence on the evolution of a subfield (e.g., foundation models, multimodal learning, reasoning systems, or model efficiency) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $350,000 - $399,500 for Sr. Staff Applied Researcher McLean, VA: $350,000 - $399,500 for Sr. Staff Applied Researcher New York, NY: $381,800 - $435,700 for Sr. Staff Applied Researcher San Francisco, CA: $381,800 - $435,700 for Sr. Staff Applied Researcher San Jose, CA: $381,800 - $435,700 for Sr. Staff Applied Researcher Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (Gen AI Platform Services: Agentic AI) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You’ll Do: • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One., • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc., • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more., • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems., • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One., • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud), • Experience designing, developing, delivering, and supporting complex AI systems, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost, • Experience in building agentic AI systems and agentic workflows, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 4 (LLM Gateway, FM Hosting) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You’ll Do: • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One., • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc., • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more., • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems., • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One., • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation The Ideal Candidate: • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy, • 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud), • Experience designing, developing, delivering, and supporting AI services, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost, • Experience in building agentic AI systems and agentic workflows, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for AI Engineer 4 McLean, VA: $197,300 - $225,100 for AI Engineer 4 New York, NY: $215,200 - $245,600 for AI Engineer 4 San Jose, CA: $215,200 - $245,600 for AI Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (AI Foundations, LLM Core and Agentic AI) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You’ll Do: • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One., • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc., • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more., • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems., • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One., • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy, • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud), • Experience designing, developing, delivering, and supporting complex AI systems, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost, • Experience in building agentic AI systems and agentic workflows, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You’ll Do: • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One., • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc., • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more., • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems., • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One., • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud), • Experience designing, developing, delivering, and supporting complex AI systems, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost, • Experience in building agentic AI systems and agentic workflows, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

AI Engineer 5 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluations) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You’ll Do: • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One., • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc., • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more., • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems., • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One., • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud), • Experience designing, developing, delivering, and supporting complex AI systems, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost, • Experience in building agentic AI systems and agentic workflows, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Director, AI Engineering (Remote - eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You’ll Do: • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One., • Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc., • Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more., • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems., • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One., • Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI., • Translate the enterprise AI strategy into portfolio-level execution plans across multiple product areas, balancing innovation with delivery discipline, • Scale AI engineering practices across teams through shared infrastructure, reusable components, and unified observability and governance frameworks, • Establish enterprise standard for Responsible AI, including fairness metrics, model evaluation protocols, documentation requirements, and audit readiness, • Partner with research, compliance, and enterprise risk teams to ensure deployed systems meet emerging ethical and regulatory standards The Ideal Candidate: • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production, • You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, • At least 3 years of people leadership experience Preferred Qualifications: • 5+ years of experience managing and leading an engineering team, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud), • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang, • Experience in building agentic AI systems and agentic workflows, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers, • Experience building and leading multi-team AI organization delivering multiple enterprise products or capabilities concurrently, • Proven ability to expand and execute long-term AI platform strategies aligned to enterprise priorities and regulatory frameworks, • Experience establishing cross-functional operating rhythms and review cadences (OKRs, AI governance councils, quarterly reviews), • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $244,700 - $279,200 for Director, AI Engineer McLean, VA: $269,100 - $307,200 for Director, AI Engineer New York, NY: $293,600 - $335,100 for Director, AI Engineer San Francisco, CA: $293,600 - $335,100 for Director, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Staff AI Engineer - Enterprise Analysis Platform (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is currently working on building a new AI native platform to empower our broader business community to execute AI assisted analysis across our many lines of business. We are building an AI native, at-scale (15,000+ users at destination), enterprise platform intertwining deterministic code with non-deterministic reasoning systems as well as both frontier and home grown AI models, to transform how our company works in the data analysis space. What You’ll Do: • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One., • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc., • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more., • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems., • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One., • Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams, • Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads, • Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design, • Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds The Ideal Candidate: • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, • At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: • Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy, • 8+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud), • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost, • Experience in building agentic AI systems and agentic workflows, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers, • Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks, • Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency, • Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization, • Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $244,700 - $279,200 for Staff AI Engineer Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer McLean, VA: $269,100 - $307,200 for Staff AI Engineer New York, NY: $293,600 - $335,100 for Staff AI Engineer San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer San Jose, CA: $293,600 - $335,100 for Staff AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).