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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 \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 • \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 • \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 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).

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 (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).

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).

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 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).

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).

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 (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 \n Team Description: \n \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\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 \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 \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 \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 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).

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 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 \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 (Gen AI Platform Services)\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 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 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).

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).

Staff AI Engineer - Enterprise Analysis 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: 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.\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 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).

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).

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).

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).

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 Capital One is open to hiring a Remote Employee for this opportunity. \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 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).

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).

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).

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 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 4 (AI Foundations, LLM Customization and Finetuning)\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 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).

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).

About the Role: Join TD SYNNEX as a Field Service Technician and play a critical role in keeping our clients' technology running smoothly. In this hands-on position, you will diagnose, repair, and maintain computer hardware systems across customer locations. This is an excellent opportunity for early-career IT professionals looking to build technical expertise, gain field experience, and grow into advanced engineering or infrastructure roles. To succeed in this role, you must currently reside within a 45-minute commute of one of the following areas: Fairfield, CA (within 25 mile radius) Long Island, NY (Zip 11779) Charlotte, NC Chicago, IL Houston, TX Tampa, FL Orlando, FL What You'll Do: • Diagnose, troubleshoot, and repair computer hardware and system components in line with manufacturer specifications, • Replace defective parts and perform hardware installations and upgrades, • Collect and communicate technical data to support teams for escalations and project planning, • Follow established service procedures, documentation standards, and daily administrative processes, • Deliver excellent on-site support and maintain positive client relationships What We're Looking For: We're looking for candidates who are driven, reliable, and eager to develop their careers in IT field services. Required Qualifications • 1-2 years of experience in IT support, field services, or hardware repair Preferred Qualifications • CompTIA A+, Network+, or equivalent OEM certifications, • Experience working in customer-facing technical roles, • Strong working knowledge of:, • Computer systems and operating systems, • Networking hardware and cabling standards, • Servers, data center equipment, and power supplies, • Ability to diagnose, repair, test, and replace hardware components confidently, • Valid Driver's License with a clean driving record, • Access to a reliable personal vehicle (mileage reimbursed) Working Conditions: This position involves frequent travel and physical activity. Candidates should be comfortable with: • Local and occasional long-distance travel, including potential air travel, • Working in tight or confined spaces (e.g., under desks, kiosks, or counters), • Climbing ladders (up to 12 feet), • Bending, lifting, and moving equipment (up to 75 lbs unassisted), • Participating in on-call rotations and after-hours support Salary Range Requirement Actual annual compensation offered will be based on several variables including geographic location, work experience, education and skills/ achievements, and will be mutually agreed upon at the time of offer. • Qualified candidates can expect an hourly rate beginning at $26.00 or more depending on experience and geographical area. At Shyft Global Services, a TD SYNNEX Company, our values guide everything we do: Together, We Own It, We Dare to Go, We Grow and Win, and above all, We Do the Right Thing. These principles shape how we work with each other, our partners, and our communities as we drive innovation and create lasting impact. What's In It For You? • Elective Benefits: Our programs are tailored to your country to best accommodate your lifestyle., • Grow Your Career: Accelerate your path to success (and keep up with the future) with formal programs on leadership and professional development, and many more on-demand courses., • Elevate Your Personal Well-Being: Boost your financial, physical, and mental well-being through seminars, events, and our global Life Empowerment Assistance Program., • Diversity, Equity & Inclusion: It's not just a phrase to us; valuing every voice is how we succeed. Join us in celebrating our global diversity through inclusive education, meaningful peer-to-peer conversations, and equitable growth and development opportunities., • Make the Most of our Global Organization: Network with other new co-workers within your first 30 days through our onboarding program., • Connect with Your Community: Participate in internal, peer-led inclusive communities and activities, including business resource groups, local volunteering events, and more environmental and social initiatives. Don't meet every single requirement? Apply anyway. At Shyft Global Services, a TD SYNNEX Company, we're proud to be recognized as a great place to work and a leader in the promotion and practice of diversity, equity and inclusion. If you're excited about working for our company and believe you're a good fit for this role, we encourage you to apply. You may be exactly the person we're looking for! We are an equal opportunity employer and committed to building a team that represents and empowers a variety of backgrounds, perspectives, and skills. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, gender identity or expression, sexual orientation, protected veteran status, disability, genetics, age, or any other characteristic protected by law.

AI Engineer 4 (AI Foundations: Benchmarking, Evaluation, and Explainability)\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 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).

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).

Overview: WHY COOLSYS? At CoolSys, we offer more than just a job—we provide stability, growth, and industry-leading benefits for our employees. No wonder Newsweek named CoolSys one of America’s Greatest Workplaces! As a large company serving diverse customers, we invest in our team with: • Competitive Compensation: $45-$58 depending on experience, • Ongoing Education & Training: Access to state-of-the-art facilities and paid online training., • Comprehensive Benefits: Medical, Dental, Vision, and Prescription coverage, paid vacation/holidays, and a 401(K) match., • Year-Round, Diverse Work: Stay engaged with consistent, interesting projects throughout the year, working across various industries and systems to keep learning and growing., • Extra Perks: Quarterly bonus plan, tuition reimbursement, employee discounts on vehicles, hotels, theme parks, pet insurance, and more. Join us and advance your career while working with top-tier clients in the HVAC and refrigeration industry! Responsibilities: • Must be thoroughly familiar and have detailed knowledge of all aspects of our product offerings including CHP and Balance of Plant (including not limited to HRSG, radiators, steam/hydronic boiler, absorption chiller, chiller, standby generators, automatic transfer switches, switchgear), island and parallel operation, Comap control system, Building Management Systems, all regarding assembly, repair, wiring, re-building, testing, and troubleshooting., • Regularly travel to jobsite locations to perform preventive maintenance, corrective maintenance, unscheduled service, and troubleshooting, mechanical & electrical repairs on natural gas and biogas engines, generator sets, CHP power generation equipment, and related equipment., • Monitoring system performance via remote control on-line, diagnoses technical malfunctions / operator errors, and provides solutions., • Interface with system operators/field technicians and provides technical guidance., • Performance of engine overhauls, electrical & mechanical testing, calibration and commissioning., • Must provide clear and concise reports of all work performed daily for both internal and external reporting, observe and report conditions that could result in unscheduled or corrective maintenance, and communicate in a timely manner., • Maintain designated project & service records, and practice consistent record keeping., • Contribute to a pleasant and positive work atmosphere where all team members feel important and responsible., • Adapt to the diverse needs of a small team and address internal and external requirements with flexibility and creativity., • Regularly improve and update product knowledge by participating in educational and product training opportunities., • This description contains information necessary to describe and evaluate the job. It should not be construed as a detailed description of all work performed but indicates the kinds of duties and skills expected. The position must complete other work tasks as assigned. Qualifications:, • The candidate must have a strong reciprocating engine and electrical background with the ability to display a high level of skill and understanding regarding internal combustion engines, generator sets, ideally natural gas engines, but will consider applicants that have experience with diesel standby or other engine technologies (e.g. compression engines)., • Will also consider technicians that have a more holistic background and excellent experience and track record around complex technologies like aircraft engines and turbines., • Be able to complete technical start-up of gas engines and CHP power systems., • Independently diagnose and repair power systems., • Basic working knowledge of advanced controls, safety shut-downs, circuit breakers and control panel wiring., • Must be available to work over-time and occasionally travel on weekends., • Must be able and willing to travel., • Must be able to work independently., • Excellent written and verbal communication skills and demonstrated proficiency composing written communications., • Outstanding interpersonal skills., • Excellent telephone skills and computer knowledge., • High energy level, comfortable performing multifaceted projects in conjunction with day-to-day activities., • Resourceful, well organized, highly dependable, efficient and detail oriented., • Must present a positive, professional, and team player attitude., • Must be flexible and able to adapt to change quickly., • Must possess a valid driver’s license, • Experience and knowledge of IP Networking including troubleshooting Join Us: Today, there are 27 different companies that make up the CoolSys family of brands. Our valued employees are at the heart of our continued growth and success. We invite you to be part of that growth! Connect with us on and . CoolSys is an EEO/AA Employer. All qualified individuals - Including all ages, colors, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other characteristics are encouraged to apply. Pre-employment background screening (criminal and MVR for driving positions) and drug testing are required for all positions. CoolSys will consider qualified applicants with criminal histories in a manner consistent with federal law, state law, or local ordinance. Sr, senior, Service Tech, refridgeration, HVAC, refrigeration, HVAC-R, HVAC/R, diagnostic, commercial, service, install, mechanical, mechanic, apprentice, AC, field service, chiller, specialist, HVACR, supermarket, rack systems

AI Engineer 5 (Gen AI Platform Services - 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 • \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).

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).

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).

Process Automation & Integration Engineer Location: 620 Foster Ave, Brooklyn, NY 11230 We’re seeking a highly motivated, hands-on Process Automation & Integration Engineer to lead the design and implementation of automation solutions that streamline operations, reduce manual work, and improve how systems and teams connect. This role sits at the intersection of technology, process design, and healthcare delivery. You'll work closely with stakeholders across departments, from patient-facing teams to operational staff, to analyze workflows, identify inefficiencies, and drive process redesign using systems thinking and automation strategy. From there, you’ll implement solutions that integrate systems, orchestrate logic, and move data efficiently and securely. You’ll be expected to map processes, design target state workflows and solutions, write code, build automation that reduces friction and enhances both clinical and operational experience. You’ll also play a key role in helping us explore and adopt intelligent and agentic automation where it brings meaningful value. This role requires strong business process design capabilities, excellent technical skills (Python, APIs, data handling), and the ability to collaborate cross-functionally to turn business needs into scalable, reliable automation solutions in a healthcare context. Responsibilities Business Process Design & Analysis (25%) • Partner with stakeholders across departments to understand, map, and document existing workflows, • Analyze workflows across clinical care, patient services, and administrative operations to identify opportunities for optimization and automation, • Apply design thinking principles to develop user-centered automation workflows., • Use systems thinking to consider inter-dependencies and identify systemic solutions, • Lead process redesign efforts to optimize and prepare for automation, • Create clear solution documentation using tools like BPMN, journey maps, and user stories Automation & Integration Implementation (35%) • Design and implement scalable automation workflows using platforms such as Power Automate, • Write code and scripts (Python, JavaScript, PowerShell, etc) to support logic and integrations, • Develop and maintain system integrations via REST APIs, webhooks, and ETL pipelines, • Own the full automation lifecycle: build, test, deploy, monitor, and improve, • Ensure solutions are secure, scalable, maintainable, and performance optimized Systems Integration & Data Workflows (15%) • Work with both structured and unstructured data to support automation outcomes, • Design and implement lightweight ETL processes and automated data pipelines, • Ensure data accuracy, transformation, and compliance, including HIPAA where applicable, • Collaborate with infrastructure and data teams to align with enterprise standards, • Troubleshoot integration and data flow issues, building resilient, long-term solutions AI & Agentic Automation Readiness (10%) • Identify opportunities for AI-assisted automation (e.g., LLMs, decision engines), • Contribute to pilots and proof-of-concepts for intelligent or agentic automation use cases, • Support the evolution of the organization’s automation roadmap toward AI enhanced solutions Cross-Functional Collaboration and Support (10%) • Translate technical concepts for non-technical audiences and stakeholders, • Work collaboratively with IT, operations, and business users through the automation lifecycle, • Provide documentation, training, and support for end-users of automation solutions, • Oversee project delivery, timelines, and stakeholder communications Leadership & Advisory (5%) • Serve as a subject matter expert in automation, integration, and business process optimization, • Provide strategic input into automation standards, best practices, and emerging technologies, • Establish standards, templates, governance frameworks, and quality checks to ensure consistent, scalable automation across the organization, • Contribute to roadmap planning and organizational maturity in automation and integration strategy, • Champion a culture of safe, scalable, and sustainable automation practices Qualifications Required • 4–6 years of experience in automation, integration, or business process engineering, • Proven track record in business process design and systems thinking, • Proficient in process mapping/documentation tools (e.g., Microsoft Visio, Lucidchart, or similar), • Hands-on experience with automation platforms like Power Automate, Make, or Zapier, • Proficiency in scripting or programming languages (e.g., Python, JavaScript, PowerShell), • Experience with system integrations, APIs, data workflows, and error handling, • Strong skills in data pipeline design, ETL development, and secure data management, • Ability to analyze complex requirements and translate them into scalable solutions, • Excellent communication and collaboration skills with cross-functional teams, • Highly detail-oriented, results-driven, and committed to continuous learning, • Comfortable managing multiple projects in a fast-paced environment Preferred • Familiarity with intelligent automation technologies (e.g., OCR, NLP, LLMs, AI agents), • Experience working in healthcare or other regulated industries, • Exposure to low-code/no-code platforms, BPM tools, or digital transformation frameworks, • Experience with data visualization or lightweight analytics (e.g., Power BI, SQL), • Understanding of clinical workflows or patient-centered process optimization, • Familiarity with healthcare compliance and data protection standards (e.g., HIPAA) Benefits: • Public Service Loan Forgiveness (PSLF), • Paid Time Off, Medical, Dental and Vision plans, Retirement plans

About Us Surgeon Decision Intelligence (SDI) is an emerging leader in AI-driven medical imaging solutions for orthopedic care. Founded by a team of orthopedic spine surgeons and medical students from the Hospital for Special Surgery, the world’s best orthopedic hospital, our mission is to transform patient care by developing quantitative imaging biomarkers to inform treatment approaches for a broad spectrum of musculoskeletal disease and predict associated outcomes. We combine cutting-edge computer vision, medical image analysis, and machine learning to unlock new insights from MRI imaging, one of the most widely obtained modalities of medical imaging, accelerating the translation of novel imaging biomarkers from research into clinical practice. Our team is passionate about bridging the gap between advanced computational methods and real-world healthcare impact. Position Summary The Principal Software Quality Engineer is responsible for leading software quality assurance activities for our Class II AI/ML-based Software as a Medical Device (SaMD). This role provides technical leadership and quality oversight across the full software lifecycle, including design controls, risk management, verification and validation, cybersecurity, release management, post-market activities, change control, and quality system compliance. You will work closely with Software Engineering, Machine Learning, Product, Regulatory, Clinical, and Cybersecurity teams to ensure our software is developed, tested, released, maintained, and changed in a controlled, compliant, and risk-based manner that supports product safety, effectiveness, and quality, including Quality System requirements. You will also provide technical oversight, mentoring, and review of work performed by internal teams, consultants, contractors, and third-party service providers. Essential Responsibilities: The Principal Software Quality Engineer is responsible for supporting and leading software quality activities across the full product lifecycle, including design, development, verification, validation, release, maintenance, and post-market change control. Essential responsibilities include, but are not limited to, the following: · Provide software quality engineering leadership for the Company’s Class II AI/ML-based Software as a Medical Device. · Support compliance with applicable medical device software regulations, standards, guidance documents, and internal quality system procedures. · Provide Quality oversight for software lifecycle activities, including requirements, design, development, verification, validation, release, maintenance, and change control. · Review and approve software quality documentation, including software requirements, design documentation, risk analyses, cybersecurity risk analyses, traceability matrices, verification protocols, validation protocols, test reports, release documentation, and change records. · Ensure software requirements are clear, testable, traceable, risk-based, and aligned with user needs and intended use. · Support design control activities, including design inputs, design outputs, design reviews, design verification, design validation, design transfer, and design changes. · Ensure appropriate traceability among requirements, design outputs, risk controls, verification testing, validation testing, defects, and released software. · Provide quality oversight for AI/ML-related software activities, including algorithm performance documentation, dataset considerations, acceptance criteria, validation activities, and change impact assessments. · Support software verification and validation activities, including test plans, test cases, automated testing, regression testing, performance testing, cybersecurity testing, deviations, anomalies, and final reports. · Evaluate software defects, deviations, and unresolved anomalies for safety, performance, cybersecurity, regulatory, and release impact. · Support software release readiness reviews and confirm required testing, documentation, risk assessments, cybersecurity activities, and approvals are complete. · Review and approve software change requests and impact assessments, including impact to requirements, risk management, cybersecurity, validation, labeling, and regulatory documentation. · Provide quality oversight for cloud-based software deployment, configuration management, access controls, release controls, CI/CD processes, source code repositories, and software development tools. · Support cybersecurity quality activities, including review of threat models, vulnerability assessments, penetration testing results, SBOM documentation, vulnerability dispositions, and cybersecurity risk mitigations. · Support supplier quality activities for software-related suppliers, cloud service providers, software development contractors, cybersecurity vendors, and other third-party service providers. · Support post-market software quality activities, including complaint investigations, CAPA, nonconformances, field issues, software patches, and maintenance releases. · Provide quality input for regulatory submissions and responses to regulatory questions related to software, cybersecurity, risk management, and verification and validation. · Participate in internal audits, external audits, supplier audits, and regulatory inspections related to software quality and SaMD development. · Identify and support improvements to software quality processes, design controls, risk management, verification and validation, cybersecurity, and release management. · Mentor cross-functional team members on software quality expectations, documentation practices, risk-based thinking, and medical device software compliance. · Oversee our cloud infrastructure (Azure/AWS), CI/CD pipelines, and DevSecOps practices. Minimum Qualifications: To be qualified for this role, the Principal Software Quality Engineer shall meet the following requirements: · Bachelor’s degree in Software Engineering, Computer Science, Biomedical Engineering, Electrical Engineering, Systems Engineering, or a related technical discipline. · Minimum of 8 years of experience in software quality engineering, software development, software verification and validation, quality engineering, or related medical device software role. · Minimum of 5 years of experience working in a regulated medical device, SaMD, digital health, diagnostic imaging, healthcare software, or other regulated life sciences environment. · Demonstrated knowledge of medical device design controls and software lifecycle requirements. · Demonstrated knowledge of the US FDA’s expectations for maintaining AI/ML-enabled medical devices including predetermined change control plans, real-world performance monitoring, and algorithm change management. · Experience with software verification and validation, including review of test plans, protocols, test cases, test results, deviations, anomalies, and traceability. · Experience with risk management for medical devices, including hazard analysis, software risk analysis, cybersecurity risk analysis, and risk control verification. · Working knowledge of applicable standards and regulations, such as 21 CFR Part 820, ISO 13485, ISO 14971, IEC 62304, IEC 62366-1, and FDA guidance for medical device software. · Experience supporting software change control, release readiness, configuration management, and defect management. · Experience working with cross-functional teams, including software engineering, product, regulatory, clinical, cybersecurity, and quality. · Strong technical writing skills, including ability to write and review clear, complete, and audit-ready quality records. · Strong analytical and problem-solving skills, including ability to assess technical issues for quality, safety, cybersecurity, regulatory, and business impact. · Ability to work independently, prioritize work, and provide technical leadership in a fast-paced development environment. · Proficiency in English, including ability to read, write, review, and approve technical and quality documentation. Preferred qualifications include: · Master’s degree in Software Engineering, Computer Science, Biomedical Engineering, Regulatory Science, Quality Assurance, or a related discipline. · Experience with AI/ML-enabled medical devices, imaging software, quantitative imaging biomarkers, radiology workflows, MRI image processing, or clinical decision-support software. · Experience with Class II SaMD regulatory submissions, including US FDA 510(k) submissions. · Experience with cloud-based software platforms and Microsoft Azure. · Experience with cybersecurity documentation for medical devices, including threat modeling, SBOM review, vulnerability assessment, penetration testing, and cybersecurity risk management. · Experience with automated testing frameworks, CI/CD pipelines, DevOps practices, GitHub, Jira, Azure DevOps, or similar tools. · Experience with software tool validation or computer software assurance. · Experience supporting US FDA inspections, ISO 13485 audits, MDSAP audits, supplier audits, or EU notified body audits. · ASQ Certified Software Quality Engineer, Certified Quality Engineer, Regulatory Affairs Certification, or similar professional certification. Location Remote (U.S.) temporarily, but able to transition to in-person work in New York City in approximately 6 months. Compensation Highly competitive salary + equity + benefits, commensurate with experience. If you’re excited about our mission, we want to hear from you. The base salary for this role is $200,000 - 270,000. How to Apply • If you’re excited to help shape the future of quantitative imaging biomarkers and medical AI, send your resume and a brief introduction to nathooi@sdi-global.ai (Isaac).

Faction Imaging is seeking an experienced Electrical Engineer to help accelerate the development of next-generation medical imaging solutions. In this role, you will work with a multidisciplinary team of engineers and contribute to the design, integration, and validation of robust, production-quality hardware systems that enable efficient and reliable execution of critical medical procedures performed millions of times each year. Core Responsibilities • Architect, design, and integrate electronic systems for a platform, including electromechanical actuators, power distribution, communication interfaces, and subsystems involving high-density, impedance-controlled, low-noise RF signaling, • Own the end-to-end lifecycle of electronic designs, defining system architectures and interfaces across motors, sensors, embedded computing, and safety-critical electronics from concept through validation, • Collaborate closely with mechanical, controls, and systems engineers, as well as industrial designers, to manage cross-disciplinary tradeoffs and ensure cohesive system integration, • Support manufacturing, assembly, and test builds, including documentation, troubleshooting, and design refinement, • Provide technical input and system-level guidance for the integration of specialized sensing electronics, coordinating with external experts as needed Required Qualifications • Bachelor’s degree in Electrical Engineering or a closely related field, • 5+ years of experience designing and integrating electronic systems for robotics, distributed systems, or complex electromechanical products, • Demonstrated proficiency with PCB schematic capture and board layout using professional eCAD tools (e.g., Altium, Allegro, or equivalent), • Experience with network and fieldbus protocols such as EtherCAT and CAN, as well as embedded serial protocols including SPI and I²C, • Hands-on experience with hardware bring-up, debugging, and validation using standard lab instrumentation, • Experience designing flexible printed circuits, specifying connectors and cabling, and addressing EMI/ESD and signal integrity challenges Preferred Qualifications • Experience developing electronics for medical devices, including familiarity with IEC 60601-1 (or experience in other regulated, safety-critical environments such as aerospace), • Familiarity with system-level documentation such as functional specifications, design verification plans, and test procedures, • Working knowledge of mechanical CAD tools (e.g., SolidWorks) to support collaborative integration with mechanical designs, • Experience supporting manufacturing transfer, supplier engagement, and early production builds, • Experience with power electronics, power distribution, and battery systems This is a part-time hybrid position, which will require time in Faction’s office in downtown Manhattan.

We’re looking for an experienced Senior RF Wireless Engineer to design, survey, and optimize enterprise wireless networks. This role includes RF planning, predictive and physical site surveys, troubleshooting wireless performance, and supporting Cisco wireless infrastructure. Requirements • 5+ years of RF wireless engineering experience, • Strong RF design and site survey experience (Ekahau, spectrum analyzers), • Experience with Cisco wireless access points and controllers, • Knowledge of LAN/WAN, DNS, DHCP, VPN, and network security, • Experience troubleshooting wireless and network performance Preferred • CCNP or CWNP certification, • Experience with RF design tools (Visio, AutoCAD)

Job Summary: The purpose of this position is to execute packaging development initiatives from concept to commercialization while working closely with cross-functional partners. The primary project work typically will include new packaging growth programs, productivity initiatives and quality improvements. The Packaging Engineer is responsible for a variety of packaging projects across multiple formats and for multiple products. The incumbent will have contact with packaging material suppliers in the USA as well as overseas and will be required to coordinate project activities with all these suppliers simultaneously at times. Responsibilities: • Responsible for format expansions across all packaging categories to support new launches and engineering leads, • Work with vendors and marketing team members to develop packs, developing best practice packaging processes, finalizing specifications, managing overall quality and package functionality, • Discover new products/technology to “raise the bar” in packaging for innovation and sustainability goals, • Manage technical timelines for projects providing timely communication, outlining issues, risks and contingency plans, • Develop written testing protocols and complete thorough plant trials for various products lines, • Collaborate with Quality team to problem solve and troubleshoot when deviations occur in production, • Develop and maintain a professional knowledge of new or emerging trends within the packaging discipline, • Accountable for the creation and maintenance of packaging component specifications and finished good assembly instructions, • Work in conjunction with Creative and Marketing to design and develop eye catching packaging that will contribute to sales growth Requirements: • Bachelor’s degree in Packaging Engineering, Chemical Engineering or Mechanical Engineering or the equivalent relevant experience, • 1-3 years’ experience, ideally in Beauty and/or CPG environment, • Ability and willingness to learn new technical areas leveraging internal and external resources, • Strong organizational and communication skills Company Summary: eos Products is an iconic beauty brand founded on an innovative and entrepreneurial spirit that revolutionized how people experience daily beauty routines. As a brand of choice among gen z and millennial consumers, eos aims to drive everyday experiences forward, creating the joy that beautifully designed, expertly crafted products can bring to people’s lives. From our iconic lip balm to our cult-favorite body lotion, eos products create delight where there was once utility, happiness where there was only function. Equal Opportunity Employer: eos Products offers equal employment opportunity to qualified individuals without regard to race, religion, color, national origin, age, gender, disability, medical condition, sexual orientation, gender identity, gender expression, marital status, veteran status, or any other characteristic protected by law. Minorities, women, veterans, and individuals with disabilities are encouraged to apply. FLSA Status: FLSA exempt.

Faction Imaging is building the intelligence that allows robots to autonomously interact with the human body to collect rich medical data. We're looking for a resourceful and hard-working Robotics Machine Learning Engineer to test, evaluate and improve machine learning systems on real robotic platforms. You'll work closely with experienced engineers to design experiments, benchmark new approaches, and improve the performance and reliability of autonomous systems. What We're Looking For • Experience operating and testing autonomous robotic systems in a lab environment, • Experience collecting and analyzing data with statistical methods, • Experience with common robotics sensing hardware: RGB cameras, depth cameras, force sensors, tracking systems, etc., • Experience with real time publish/subscribe communication protocols (e.g. ROS 2), • Experience with multi-threading and asynchronous python, • Experience with modern machine learning methods for robotic control: behavior cloning, reinforcement learning, or related learning methods, • Extensive experience with the python programming language and related machine learning libraries, • Experience in autonomous navigation is a major plus, • Familiarity with real time robotic control systems is a plus Job Details Faction is located in downtown Manhattan, New York City. This is an in-person job requiring significant percentage of your time on-site. Why Faction Faction is tackling a frontier problem in Physical AI: creating robots that can safely perceive and directly interact with the human body. You'll work alongside experienced engineers on real robotic systems and contribute directly to the mission of expanding access to high-quality medical care.

Senior Wireless Network Architect We are seeking a Senior Wireless Network Architect to lead the architecture, design, implementation, and support of enterprise wireless infrastructure. This role focuses on modern wireless networks, RF surveys, deployment, optimization, and ensuring high performance and reliability across large-scale environments. Key Responsibilities • Architect, design, implement, and support enterprise wireless networks, • Conduct wireless site surveys, testing, and network optimization, • Troubleshoot complex wireless/network issues and provide Tier-3 support, • Collaborate with IT and business teams to align wireless solutions with organizational needs, • Maintain documentation, standards, and knowledge transfer for wireless implementations, • Monitor performance and manage upgrades to wireless infrastructure Required Skills • 10+ years of wireless networking experience in large enterprise environments, • Strong experience with Cisco wireless infrastructure (Catalyst access points and controllers), • Knowledge of Wi-Fi technologies, RF design, and site survey tools (Ekahau, spectrum analyzers), • Strong understanding of LAN/WAN networking, DNS, DHCP, TCP/IP, RADIUS, and network security, • Experience troubleshooting across OSI layers and network performance analysis Preferred • CCIE Wireless or similar advanced certification

EUC Engineer, Endpoint Engineer, Browser Engineer, Workplace Technology Engineer, or Windows/Citrix EUC Specialist. The ideal candidate is an EUC/Endpoint Engineer at heart with deep expertise in identity, network, and browser-level policies, backed by modern automation skills and SRE/DevOps discipl

Associate Architect | Real Estate Investment Firm | Hybrid – Strong Benefits We’re working with a leading real estate investment and development firm seeking an Associate Architect to join its development team. This is a hands-on opportunity for an architect with strong design sensibility and technical experience to work on high-profile commercial and high-end residential projects in New York. The Associate Architect will partner closely with the Development team, coordinating outside design professionals and consultants while helping guide projects from early design development through completion. The role will have meaningful involvement in design direction, construction documentation, project coordination, and field execution. Key Responsibilities: • Manage high-profile projects through construction, • Lead coordination with outside architects and engineers, • Manage consultants, vendors, and project teams throughout design and construction, • Review design presentations and provide client feedback, • Assist with scopes of work, RFPs, schedules, and project planning, • Monitor project scope, schedules, budgets, and work plans, • Support construction administration and field execution, • Work closely with the Head of Development on creative direction and project strategy, • Assist with organizational initiatives, including meeting follow-ups and action-item tracking Qualifications & Experience • 4+ years of professional architecture experience following completion of an undergraduate or graduate degree, • Experience supporting commercial, luxury residential, or other high-end development projects, • Strong understanding of design development, space planning, and architectural documentation, • Comfortable coordinating multiple project stakeholders, including consultants, outside design teams, and vendors, • Hands-on knowledge of construction documentation and project administration through the construction phase, • Highly organized with strong communication, problem-solving, and project management abilities, • Advanced proficiency with AutoCAD, Bluebeam, Microsoft Office, and 3D design/modeling platforms, • Experience with Adobe Creative Suite and Revit is a plus, • Bachelor’s or Master’s degree in Architecture required Compensation: $120k-$150k plus benefits, 401k and other perks! The above salary range represents Advice's good faith and reasonable estimate of the possible base compensation range at the time of posting and is not reflective of the total compensation package, which may also include benefits, equity and other non-cash incentives. Please send your resume for immediate consideration to: ageorge@adviceny.com If this particular role isn’t the right fit, please feel free to send your resume to the email above so we can keep you in mind for other opportunities. And if you know someone in your network who may be interested, please feel free to share the posting with them. Referrals are always appreciated. Advice Personnel *Celebrating 40 years as New York’s trusted boutique executive recruiting & staffing firm

I'm working with one of the fastest-growing companies in the AI infrastructure and data center market as they undertake a major expansion of their US construction team. This business is delivering an enormous pipeline of high-density, mission-critical data center projects and is looking for experienced Construction Managers to take ownership of individual sites. This isn't a traditional construction management environment. The objective is simple: build faster, remove unnecessary process and find better ways to deliver mission-critical infrastructure at scale. The Role You'll take ownership of day-to-day construction delivery on a major data center project, working across greenfield and brownfield developments and coordinating GCs, subcontractors, vendors and internal teams. You'll be responsible for: • Managing site execution from construction through commissioning and turnover, • Coordinating CSA and MEP packages and resolving field issues quickly, • Driving integrated schedules using Primavera P6 and/or MS Project, • Managing contractors, critical-path scopes and construction packages, • Monitoring schedule, cost, progress and resource requirements, • Managing RFIs, submittals, change orders and QA/QC, • Working closely with Design, Procurement, Commissioning and Operations, • Maintaining an uncompromising approach to site safety, • Identifying delays early and implementing recovery plans What We're Looking For We're particularly interested in Construction Managers with experience delivering: • Hyperscale / Data Centers, • Mission-Critical Facilities, • Semiconductor / Advanced Manufacturing You'll need a strong understanding of MEP and CSA construction, scheduling, procurement, cost control and contractor management. Experience with high-density electrical infrastructure, liquid cooling or major power projects would be particularly valuable. Important – Travel This is a site-driven position requiring Monday–Friday travel to your assigned project. Current projects are located across Texas, Louisiana, Indiana and New York, and all project travel is booked and paid for by the company. You can be based elsewhere in the US, but you must be genuinely comfortable traveling every week. Why Consider It? This is an opportunity to join a heavily funded, rapidly scaling business operating at the intersection of AI, energy, construction and data center infrastructure. They're not looking to build one data center. They're building a construction platform capable of delivering major infrastructure projects repeatedly and at national scale. What's on offer? • Base salary between $155k - $210lk, • Equity from day 1 with only 4-year vesting period., • Healthcare, dental, vision, • Paid travel and per diem, • Major hyper scale projects across the US If you've delivered complex mission-critical construction and want to work on some of the most ambitious infrastructure projects currently being developed in the US, I'd like to hear from you.

Lead. Grow. Build the Future. A well-established NYC-based mechanical & civil contractor is looking for a Project Executive to join its leadership team and take ownership of a major program of work. This is a high-impact position for a proven construction leader who wants more than just another project, you’ll have a seat at the leadership table, influence company strategy, develop teams, and help shape the next stage of the business. The Role: • Lead a portfolio/program of complex heavy mechanical construction projects, • Oversee Project Managers, Superintendents and project teams, • Drive financial performance, schedule, quality and client relationships, • Develop and implement operational strategy and processes, • Partner directly with company leadership on growth and business development, • Mentor and develop the next generation of leaders What We're Looking For: • 15+ years of construction experience, ideally within Heavy Mechanical / Heavy Civil industry, • Proven experience leading multiple large-scale projects or programs, • Strong commercial and operational understanding, • Excellent leadership, communication and client management skills, • NYC construction experience strongly preferred What’s On Offer: 💰 Up to $250K base + bonus 📍 NYC-based 🏗️ Senior leadership position 📈 Genuine opportunity to influence and grow the business 🤝 Direct access to company ownership and executive leadership If you're an experienced Project Executive, Operations Executive, Senior PM or Division Leader ready for a true leadership opportunity, apply now or reach out to me directly.

Rotating Equipment Engineer – Linden, NJ Seeking a Rotating Equipment Engineer to support operations and maintenance at a major chemical manufacturing facility in Linden, NJ. • Provide engineering support for pumps, compressors, turbines, gearboxes, and other rotating equipment., • Troubleshoot equipment issues, conduct failure analysis, and recommend reliability improvements., • Support maintenance, inspections, equipment upgrades, and capital projects., • Develop technical specifications, review vendor documentation, and work with maintenance and operations teams. Requirements: Bachelor’s degree in Mechanical Engineering or related field, with experience in rotating equipment within chemical, petrochemical, refinery, or industrial manufacturing environments. Experience with reliability engineering and predictive maintenance is a plus.

Does working in a green industry provide satisfaction and fulfillment? Would you like to be part of a dedicated, highly skilled and tightly knit team? Do you have experience in the design of efficient, cost-effective digital controls for HVAC, Access or Security? Then come work for us! The Company Since the industry began, TMBA has specialized in providing turnkey Building Management/Automation Systems and Energy Cost Reduction Measures. We provide innovative design, installation and true 24/7 service to our commercial, industrial and institutional clients. Our intensely loyal customer base is testament to TMBA’s quality product and dedicated service and is the nucleus for our steady growth. Responsibilities • Designs and configures complex building automation and HVAC control systems including integration to other low voltage systems., • Selects hardware, transducers and other components required to interface with controlled equipment., • Provides detailed information to communicate design intent to customers and subcontractors including flow diagrams, point to point wiring diagrams, riser diagrams, IO summaries, sequences of operation, equipment schedules, and product data sheets., • Completes project layout based on proposal, specifications and discussion with sales engineers and project engineers., • Coordinates field changes from the project team to create as-built drawings., • Prepares proper documentation and/or manuals for systems operation., • Participates in meetings with consulting engineers and project owners to resolve conflicts. Requirements • Bachelor’s degree in mechanical or electrical engineering or equivalent experience., • Understanding and experience in the design of HVAC Control Systems., • Ability to read & interpret mechanical and electrical drawings., • Strong verbal and written communication skills., • Design software knowledge required, AutoCAD preferred.Ability to analyze control system drawings and schedules a plus., • Schneider Electric/Andover Controls product knowledge, a plus. Work Location: Glen Cove, NY Benefits • Medical, Dental and Vision Insurance, • Life Insurance, Short-term and Long-term Disability Insurance, • Paid Time Off, Paid Holidays, • Employer Matched 401K Plan, • Profit Sharing Plan Job Type: Full-time, Exempt Annual Salary: $70,000 – $120,000, Dependent upon experience level. Job Type: Full-time Pay: $70,000.00 - $120,000.00 per year Benefits: • 401(k), • 401(k) matching, • Dental insurance, • Flexible spending account, • Health insurance, • Health savings account, • Life insurance, • Paid time off, • Vision insurance Education: Bachelor's (Required) Experience: BMS/BAS: 2 years (Preferred) Ability to Commute: Glen Cove, NY 11542 (Required) Work Location: In person