Java jobs in United States

Job DescriptionSummary: Work Mode: [Remote / On-site / Hybrid – specify] Job Type: Full-time Experience Level: Mid to Senior Level Responsibilities: • Plan, coordinate, execute, and successfully deliver projects within established timelines, budgets, and quality standards., • Develop project plans, define milestones and deliverables, assign responsibilities, manage resources, and monitor project progress., • Communicate regularly with stakeholders, identify potential risks and issues, and develop appropriate mitigation strategies., • Coordinate cross-functional teams and ensure that project objectives are clearly understood and achieved., • Maintain accurate documentation and provide regular status reports to management.Requirements:, • 5 years of professional software development experience., • Proficiency in one or more programming languages (e.g., Java, Python, C#, JavaScript/TypeScript, Go)., • Experience building and consuming RESTful APIs and/or working with microservices architecture., • Strong understanding of computer science fundamentals including data structures, algorithms, and design patterns., • Familiarity with relational and/or NoSQL databases., • Hands-on experience with version control tools (e.g., Git)., • Exposure to agile development methodologies., • Experience with testing practices (unit, integration, and end-to-end testing).Preferred Skills:, • Experience with containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes)., • Familiarity with cloud services (e.g., AWS, Azure, GCP)., • Knowledge of CI/CD pipelines and DevOps practices., • Experience with front-end technologies (e.g., React, Angular, Vue.js) if applicable to the role., • Prior involvement in codebase migration, scalability improvements, or system re-architecture.Benefits:, • Full-time role with flexible work options., • Opportunities for professional development and career growth., • Role may involve technical mentorship or leadership responsibilities.

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).

An architecture professional with broad enterprise technology knowledge who can independently research complex technical topics, analyze application and technology landscapes, develop architecture options and recommendations, and communicate findings clearly to both technical and senior audiences. \n Will not be hands on coding but needs to be technical enough to understand what changes need to be made and why. \n \n Must have Skills: \n \n Kubernetes \n Docker / OCI containers \n Linux \n Terraform \n Helm \n Git \n CI/CD platforms \n Languages like: Java, Python, .NET \n REST APIs / microservices \n Kafka / enterprise messaging \n Relational databases \n Cloud platforms: AWS / Azure / Google Cloud \n Advanced Excel, Power Point, \n Architecture diagramming tools

Machine Learning Engineer 4 - Finance Tech\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 Finance Tech is responsible for transforming Capital One's financial engine into the most trusted, nimble, and insightful in the industry. Our core mission is to engineer outcomes that strategically enable the Finance organization and the broader Enterprise to remain efficient. This mission is driven by four technical and functional pillars: Forecasting & Resiliency, providing advanced decision support; Treasury & Trade managing sophisticated cash and investment lifecycles; and Accounting & Reporting, ensuring the integrity of our general ledger and regulatory commitments. Powering these pillars are our Data and Core capabilities, which manage the orchestration, sourcing, and pipelines for critical financial data products. \n \n By defining the next generation of financial technology, we ensure that every business process is backed by high fidelity tracking and reporting. Together, we are not just supporting the bottom line - we are building a strategic enabler that operates as a world class financial engine. \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 This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. \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 Cambridge, MA: $197,300 - $225,100 for Machine Learning Engineer 4\n \n McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4\n \n New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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 Francisco, CA: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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

AI Engineer 5\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 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).

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).

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 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).

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).

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 As part of the Enterprise ML Platform team, you will build and evolve the high-throughput, multi-tenant training platform that powers model workflows across Capital One—ranging from classical ML to GenAI fine-tuning and distributed computing with Ray, Spark, and Dask. Owning the Kubeflow Pipelines v2 application layer on Amazon EKS, the team develops internal Python and Go SDKs, custom Kubernetes operators, and developer tooling that abstract complex infrastructure for critical, regulated workloads. In this role, you will integrate agentic AI into modern engineering lifecycles and contribute directly to upstream open-source Kubeflow, balancing fast-paced feature delivery with enterprise-grade platform stability and security. \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 designing, training, optimizing, and evaluating modern ML models across architectures (e.g., Transformers, CNNs, RNNs) and paradigms (supervised, unsupervised, reinforcement learning), including loss design, hyperparameter tuning, and diagnostic debugging.\n, • 3+ years architecting and scaling distributed, end-to-end ML systems, from production-ready training/evaluation data pipelines to algorithm and infrastructure optimization.\n, • 3+ years managing ML workloads using Docker, Kubernetes, and pipeline orchestration tools (e.g., Kubeflow is a strong plus).\n, • 3+ years applying modern software best practices (CI/CD, version control, automated testing, code reviews) and deploying resilient systems with progressive rollout strategies (blue/green, canary/one-box), monitoring, alerting, and incident response planning.\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 San Jose, CA: $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 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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

AI Engineer 5 (Gen AI SDK: Agentic AI, Guardrails, Evaluation)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • 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 (AI Foundations)\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, • 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 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 \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\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, • 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, • 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, • 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, • 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, • Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts\n, • Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems\n, • Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle \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 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, • 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 This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. \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 1 year of people leadership experience\n\n \n Preferred Qualifications: \n\n • 3+ years of experience managing and leading an engineering team\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 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 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 leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery\n, • Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance\n, • Track record mentoring engineers/scientists to productize prototypes and meet production SLOs\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 Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n \n \n Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. \n This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.\n \n Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. \n This role is expected to accept applications for a minimum of 5 business days.\n \n No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.\n \n \n If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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 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 Team Description: \n \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n \n What You’ll Do: \n \n\n • 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\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 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 \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).

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).

AI Engineer 5 (AI Foundations: Evaluations and Agentic Workflows)\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 This role is designated as a hybrid position. You are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. \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 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 (AI Safety and Multimodal)\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 experienced in AI red teaming and in deploying safety guardrails for multimodal systems, including VLMs, MLLMs, and MM-RAG architectures\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 AI Safety and LLM safety alignment\n, • Experience with Safety and vulnerability assessment of Multi-modal application using image/video plus text modality\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).

Sr. 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 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 \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: $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 Richmond, VA: $286,200 - $326,700 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).

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're proud to work for a mission-driven company leveraging AI to transform the way we work. CrowdStrikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation. We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover insights, and solve complex problems. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you. About the Role: CrowdStrike Falcon is the industry standard in cloud‑native cybersecurity and threat hunting, processing trillions of events per day. As a Principal SRE, you will operate at the intersection of our Core Platform and Embedded Reliability charters: building the foundational libraries, services, and tooling that every product group depends on, while embedding directly with product engineering teams and their leadership to drive reliability outcomes at scale. While we embrace the SRE moniker, at CrowdStrike it means something far more service‑oriented and engineering‑heavy than traditional operations. This is hands‑on systems engineering — writing production code, re‑architecting critical systems, and eliminating entire classes of failure — not ticket management. It is far and away our most self‑driven and autonomous backend engineering role, with the freedom to move up, down, and laterally across the stack as needed. You'll join a group with bottom‑up visibility and ownership of a fast‑expanding codebase (including AI‑based Detection & Response) and a far‑reaching mandate for service resiliency. Several key feature additions and critical re‑architecture initiatives are underway: deploying core services to additional cloud providers, modularizing into reusable components, improving core libraries and frameworks, maturing observability tooling (tracing, profiling, alerting, SLOs), and automating away manual toil across all of the above. Recent examples of the team's work include introducing adaptive concurrency into our core Kafka library to implement flow control that protects database performance, resolving critical issues in leader election libraries, and building infrastructure‑as‑code tooling that eliminated manual deployment processes. At the Senior Engineer level, your influence is organizational. Product engineers and engineering leaders will come to you for guidance on architectural decisions because you've earned credibility through hands‑on work and delivered results. You will shape architectural choices that affect every feature development team and provide shared architectural components leveraged throughout the Falcon Platform — including Unified Search, Protobuf libraries, and other shared‑tier infrastructure. Why This Role Matters: Our customers depend on us to protect their businesses from sophisticated threats, and reliability isn't optional — it's fundamental to our mission. Your work directly impacts whether organizations around the world can defend themselves against cyberattacks. You'll work on problems that matter, at a scale few companies can match, with the autonomy to make real architectural decisions. Location: This position requires candidates to be based in Midtown Manhattan, NY; Redmond, WA; Sunnyvale, CA; or Austin, TX. It's a hybrid role, with employees typically working 2 to 3 days per week in the office. What You'll Do: Partner with engineering leadership across multiple product groups to define and drive multi‑year reliability roadmaps. Design and implement architectural improvements to services, libraries, and platforms that impact teams across all of CrowdStrike. Develop and maintain services that meet aggressive reliability and scalability demands. Extend and build new libraries for cross‑cutting concerns spanning CrowdStrike's cloud platform, which comprises hundreds of libraries and services. Lead initiatives around reliability, scalability, performance, and cost efficiency in large‑scale distributed systems. Establish foundational observability practices: ensure teams instrument services properly, react to signals effectively, and leverage observability to drive automation such as continuous delivery. Define and implement service‑level objectives and error budgets that drive real decision‑making and prioritization. Lead performance and cost optimization efforts: profiling, bottleneck analysis, capacity planning, and cloud efficiency improvements. Conduct resilience engineering: chaos experiments, failure injection, failure modeling, and designing for graceful degradation. Design and implement automation and infrastructure‑as‑code to improve infrastructure reliability and eliminate manual toil. Provide technical leadership during complex incidents and ensure follow‑through on retrospectives with concrete improvements that eliminate entire classes of failures. Identify opportunities to extract common patterns into shared libraries and tools, or partner with platform teams on improvements benefiting multiple product groups. Continuously re‑evaluate our products to improve architecture, knowledge models, developer and user experience, performance, and stability. Drive strategic technical decisions and influence infrastructure and operational improvements across the organization. Mentor and coach engineers, raising the technical IQ of the team and driving architectural standards across the org. Use and give back to the open source community; evangelize software engineering best practices, especially as they pertain to Go. Brainstorm, define, and build collaboratively with members across multiple teams as an energetic self‑starter who owns and is accountable for deliverables. What You'll Need: 10+ years of experience building and operating distributed systems and service‑oriented backends at scale. 5+ years developing microservices for a SaaS product in a modern backend language (Go, Java, Scala, Kotlin, Python, Node.js). Expert‑level proficiency in at least one programming language, with expert‑level Go or demonstrated ability and willingness to reach expert level in Go. Deep understanding of distributed systems: consensus algorithms, replication, consistency models, failure modes, and scalability patterns. Proven experience scaling backend systems — sharding, partitioning, horizontal scaling, capacity planning, and performance optimization are second nature. Deep understanding of multi‑threading, concurrency, and parallel processing. Track record of making impactful architectural decisions at organizational scope and seeing them through to production. Strong systems thinking and the ability to influence without direct authority across organizational boundaries. Thorough command of engineering best practices: appropriate testing paradigms, effective peer code review, and resilient architecture. Ability to thrive in a fast‑paced, test‑driven, collaborative, and iterative environment; strong team‑player orientation. A desire to ship code and a love of seeing your bits run in production. Degree in Computer Science, or commensurate experience in data structures, algorithms, and distributed systems. Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes. Bonus Points: Experience driving reliability improvements in organizations with hundreds or thousands of microservices. Deep knowledge of Kubernetes or other large‑scale orchestration systems. Hands‑on experience with AWS, Cassandra, Kafka, Elasticsearch/OpenSearch, or similar large‑scale distributed technologies. Experience with Google Cloud Platform (GCP). Experience with Oracle Cloud Infrastructure (OCI). Experience delivering or operating services across multiple cloud providers, including multi‑cloud abstraction layers, portability, and cloud‑agnostic tooling. Track record of building internal platforms, developer platforms, or tools that other engineers depend on. Experience with infrastructure cost optimization at scale. Background in performance engineering: profiling, optimization, and identifying system bottlenecks. Experience with chaos engineering or resilience testing practices. History of establishing SLO/SLI frameworks and error budgets in production environments. Contributions to the open source community (GitHub, Stack Overflow, technical blogging). Prior experience in the cybersecurity or intelligence fields. #LI-SC1 Benefits of Working at CrowdStrike: Market leader in compensation and equity awards Comprehensive physical and mental wellness programs Competitive vacation and holidays for recharge Paid parental and adoption leaves Professional development opportunities for all employees regardless of level or role Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections Vibrant office culture with world class amenities Great Place to Work Certified™ across the globe CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program. CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements. If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at _ for further assistance. _ CrowdStrike participates in the E-Verify program. _ _ CrowdStrike, Inc. is committed to fair and equitable compensation practices. Placement within the pay range is dependent on a variety of factors including, but not limited to, relevant work experience, skills, certifications, job level, supervisory status, and location. The base salary range for this position for all U.S. candidates is $140,000 - $215,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off. For detailed information about the U.S. benefits package, please _.

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're proud to work for a mission-driven company leveraging AI to transform the way we work. CrowdStrikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation. We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover insights, and solve complex problems. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you. About the Role: CrowdStrike is seeking an Engineering Manager to join our Proactive Security team within Cloud Security Group. This role will lead our Proactive Protection team, focusing on helping our customers to detect and prevent threats in cloud environments through advanced detection techniques and methodologies, before they can cause harm. You will collaborate closely with cross-functional teams, product management, and security researchers to drive detection capabilities while building a team and managing direct reports. We're seeking innovative problem-solvers who can take ownership of complex technical challenges across our platform. This is an opportunity to work at unprecedented scale with cutting-edge cloud technologies while making a direct impact on organizations worldwide protecting them from sophisticated threats. This role is hybrid, on-site at one of the posted locations. Candidates should be comfortable visiting the office twice a week once the development center is established. About the Cloud Proactive Security Team: A global team of engineers that develops and maintains mechanisms to prevent cloud misconfigurations and security risks before deployment - The team builds intelligent prevention capabilities that identify and block insecure cloud configurations. Develops and maintains proactive security controls that protect Kubernetes clusters, container registries, serverless functions, and cloud workloads from emerging threats in multiple cloud vendors as well as private data centers. Creates developer-friendly tools and integrations that embed security prevention directly into CI/CD pipelines, GitOps workflows, and Kubernetes deployment processes. What You Will Do: Manage a team of engineers building and optimizing the core pipeline that protects cloud workloads, containers, and Kubernetes clusters. As an engineering manager, you will help drive and deliver on both roadmap and technical strategy, and you will be instrumental in hiring, retaining, and growing a team of highly talented engineers. Help to architect enterprise grade solutions that scale seamlessly from thousands to millions of requests per second Build and Lead a Global Team. Manage a distributed team of high-talented cloud specialized software engineers and technical leads, fostering a collaborative environment while coordinating across time zones to deliver high-quality products. Cross-Functional Collaboration. Partner with product management and engineering teams to align cloud proactive capabilities with customer needs, directly influencing CrowdStrike's Proactive detection platform evolution and organizational strategy. Ensure Quality and Accuracy. Own validation processes for proactive vulnerability detections, implementing automated workflows that maintain CrowdStrike's high standards for security solutions. Must be able to work 3+ days per week on site from our New York office. What You’ll Need: Must be a U.S. Citizen or US Permanent Resident. BS/MS in Computer Science or related field, or equivalent work experience 7+ years of experience in Software Engineering roles with at least 3+ years in management positions. Security and/or Cloud Security experience is required Understanding of cloud security concepts such as CSPM, CWPP, and CNAPP Exposure to cloud security products, including product direction for AI/ML, XDR, SIEM, SOAR, or related cybersecurity domains. Familiarity with container and Kubernetes security (build-time and runtime) Solid design and problem-solving skills with a demonstrated passion for engineering excellence, quality, security, and performance Broad grounding in all aspects of distributed systems development Experience with Kafka, Cassandra, ElasticSearch technologies Experience building systems at cloud scale and container orchestration technologies such as Kubernetes Proficiency with at least one major cloud platform (AWS, Azure, or GCP) Experience with modern programming languages such as Go, Python, Java, C++, Rust or similar languages Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes. Exceptional communication skills, with the ability to convey complex technical concepts clearly to both executive and engineering audiences, in writing and verbally Strong cross-functional collaboration skills, with a proven ability to partner effectively across engineering, product management, support, and sales engineering Demonstrated success recruiting and hiring strong engineering talent Proven track record of mentoring and developing engineers, helping them grow in their careers and technical skills Bonus Points: Remote/distributed multi-team leadership experience Experience with organizational scaling and process optimization #LI-JC1 This role will require the candidate to periodically undergo and pass additional background and fingerprint check(s) consistent with government customer requirements. Benefits of Working at CrowdStrike: Market leader in compensation and equity awards Comprehensive physical and mental wellness programs Competitive vacation and holidays for recharge Paid parental and adoption leaves Professional development opportunities for all employees regardless of level or role Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections Vibrant office culture with world class amenities Great Place to Work Certified™ across the globe CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program. CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements. If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at _ for further assistance. _ CrowdStrike participates in the E-Verify program. _ _ CrowdStrike, Inc. is committed to fair and equitable compensation practices. Placement within the pay range is dependent on a variety of factors including, but not limited to, relevant work experience, skills, certifications, job level, supervisory status, and location. The base salary range for this position for all U.S. candidates is $140,000 - $215,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off. For detailed information about the U.S. benefits package, please _.

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).

Senior Director, AI Engineering -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 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, • 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, • 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, • 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, • 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, • Define and drive enterprise-wide AI strategy, aligning product, research, risk, and data organizations around shared technical and ethical principles\n, • Establish a multi-year roadmap for scalable, reliable, and compliant AI systems that serve as shared infrastructure across the enterprise\n, • Champion Responsible-AI, ensuring ethical, transparent and explainable model practices are embedded in all lines of business\n, • Oversee the scaling of AI operations - including model lifecycle management, observability, and cost efficiency - across hundreds of production use cases\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 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, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Capital One is open to hiring a Remote or Hybrid Employee for this opportunity. If the role is designated as Hybrid, you are expected to adhere to Capital One's hybrid policy regarding required on-site presence at your designated office location. If the role is designated as Remote, you are expected to adhere to Capital One's Remote Worker Expectations \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 5 years of people leadership experience\n\n \n Preferred Qualifications: \n\n • 7+ years of experience managing and leading an engineering team\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 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 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, • Demonstrated experience leading leaders and multiple AI engineering organizations across product, platform and applied research domains\n, • Proven success in building enterprise-scale AI platforms and capabilities serving diverse business lines and customer use cases\n, • Ability to influence executive leadership on AI investment strategy, organizational design, and risk management priorities\n, • Experience establishing external partnerships or thought leadership presence in AI industry, academia, or open-source communities\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. Director, AI Engineer\n \n Cambridge, MA: $314,800 - $359,300 for Sr. Director, AI Engineer\n \n McLean, VA: $314,800 - $359,300 for Sr. Director, AI Engineer\n \n New York, NY: $343,400 - $392,000 for Sr. Director, AI Engineer\n \n San Francisco, CA: $343,400 - $392,000 for Sr. Director, AI Engineer\n \n San Jose, CA: $343,400 - $392,000 for Sr. Director, 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).

Feel free to send your resume directly to Kajal Daftary at kajal.daftary@yoh.com USC AND GC ONLY - NO SPONSORSHIP ON THIS ONE. ONLY W2, Contract to Hire, Inperson Interview Title: Senior Java Developer (Core Java, Angular 17 &20 & Oracle) Location: Jersey City, NJ LOCALS ONLY - CANNOT TAKE RELOCATION AT THIS TIME. We are seeking a highly experienced full stack Senior Java Developer to lead the design and development of scalable, high-performance, enterprise-grade full stack application in our BI & Enterprise Reporting team. This role requires deep hands-on expertise in Java/J2EE, API-driven architecture, and modern front-end frameworks (Angular), along with strong architectural and problem-solving skills.\n \n \n The ideal candidate will be responsible for translating business and technical requirements into robust application designs, driving best practices across the development lifecycle, and ensuring high-quality, secure, and maintainable solutions. This position involves close collaboration with cross-functional teams, mentoring developers, and playing a key role in technical decision-making.\n \n Main areas of responsibilities:\n \n \n\n • Lead the design, development, and implementation of Java-based, full-stack web applications - emphasis on hands on development.\n, • Architect and develop API-heavy, service-oriented and microservices-based applications using RESTful and SOAP web services.\n, • Design and document Low-Level Designs (LLD) aligned with high-level architectural standards.\n, • Apply appropriate design patterns and architectural principles to build scalable, reusable, and maintainable solutions.\n, • Develop and promote reusable components and frameworks across multiple applications.\n, • Ensure seamless integration between front-end (Angular) and back-end services.\n, • Perform code reviews, enforce coding standards, and ensure internal quality assurance for application components.\n, • Analyze and resolve complex production issues, often under tight timelines and high-pressure situations.\n, • Collaborate with product owners, business analysts, and stakeholders to understand and clarify requirements using tools such as Jira and Confluence.\n, • Support CI/CD pipelines and deployment processes in containerized and cloud-native environments.\n, • Mentor junior and mid-level developers and provide technical guidance to the development team.\n, • Continuously evaluate and recommend improvements to application architecture, performance, and security. \nRequirements:\n Experience & Skills \n\n • 10+ years of experience as a Full Stack Java/J2EE Developer, with strong exposure to analysis, design, development, and implementation of enterprise web applications.\n, • Proven expertise in applying design patterns and best practices.\n, • Strong proficiency in Core Java and object-oriented design principles.\n, • Hands-on experience preparing technical documentation, including low-level designs.\n, • Excellent problem-solving, analytical, and communication skills.\n, • Strong attention to detail and ability to troubleshoot and resolve critical issues in production environments. \nTechnical Skills \n\n • Languages: Java, J2EE, XML, SQL\n, • Technologies: Core Java, J2EE, Web Services: SOAP and RESTful APIs\n, • Web Development: HTML5, CSS3, JavaScript, jQuery, Angular 17 or above\n, • Tools & Platforms: Jenkins, Jira, IntelliJ IDEA, Apache Tomcat 9, Kubernetes, OpenShift\n, • Frameworks: Spring Boot, Hibernate\n, • Databases: Oracle (schema design, performance tuning, and efficient SQL development) \nEstimated Min Rate: $52.50\n Estimated Max Rate: $75.00\n \n What’s In It for You? We welcome you to be a part of the largest and legendary global staffing companies to meet your career aspirations. Yoh’s network of client companies has been employing professionals like you for over 65 years in the U.S., UK and Canada. Join Yoh’s extensive talent community that will provide you with access to Yoh’s vast network of opportunities and gain access to this exclusive opportunity available to you. Benefit eligibility is in accordance with applicable laws and client requirements. Benefits include:\n \n \n\n • Medical, Prescription, Dental & Vision Benefits (for employees working 20+ hours per week)\n, • Health Savings Account (HSA) (for employees working 20+ hours per week)\n, • Life & Disability Insurance (for employees working 20+ hours per week)\n, • MetLife Voluntary Benefits\n, • Employee Assistance Program (EAP)\n, • 401K Retirement Savings Plan\n, • Direct Deposit & weekly epayroll\n, • Referral Bonus Programs\n, • Certification and training opportunities \nNote: Any pay ranges displayed are estimations. Actual pay is determined by an applicant's experience, technical expertise, and other qualifications as listed in the job description. All qualified applicants are welcome to apply.\n \n \nYoh, a Day & Zimmermann company, is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.\n \n \nVisit https://www.yoh.com/applicants-with-disabilities to contact us if you are an individual with a disability and require accommodation in the application process.\n \n \nFor California applicants, qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. All of the material job duties described in this posting are job duties for which a criminal history may have a direct, adverse, and negative relationship potentially resulting in the withdrawal of a conditional offer of employment.\n \n \nIt is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.\n \n \nBy applying and submitting your resume, you authorize Yoh to review and reformat your resume to meet Yoh’s hiring clients’ preferences. To learn more about Yoh’s privacy practices, please see our Candidate Privacy Notice: https://www.yoh.com/privacy-notice Stay Safe During Your Job Search Fraudulent recruiting communications have become increasingly common. Emails from Yoh recruiters will only come from an @yoh.com email address. Yoh will never ask candidates to pay fees, purchase equipment, send gift cards, or transfer funds as part of the recruiting or hiring process. If you receive a communication that appears suspicious or requests payment, contact Yoh directly before responding or sharing personal information.

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).

Job DescriptionRole: Java Backend Developer Location: Whippany, NJ (Hybrid) Duration: Contract Job Description: Job Description: • We are seeking a Senior Java Backend Developer with strong expertise in Java, Spring Boot, Microservices, and AWS. The ideal candidate should have hands-on experience supporting production environments, troubleshooting critical issues, and working in Agile teams. Experience with AI-assisted development tools is a plus.Required Skills, • Strong experience with Java 8/11/17/21, Spring Boot, and Microservices., • Experience developing and supporting RESTful APIs and distributed systems., • Hands-on experience with AWS, OpenShift, Docker, and Kubernetes., • Strong knowledge of Agile/Scrum methodology., • Experience using AI tools (GitHub Copilot, ChatGPT, etc.) to improve development productivity., • Experience handling production support, incident management, and root cause analysis (RCA)., • Strong troubleshooting skills for memory leaks, performance bottlenecks, thread dumps, heap dumps, GC analysis, CPU utilization, and application failures., • Experience managing SSL/TLS certificates, certificate renewal, keystores, truststores, and secure application communication., • Knowledge of application monitoring and logging tools such as Splunk, ELK, Grafana, Prometheus, CloudWatch, or Dynatrace., • Experience with Git, Maven/Gradle, Jenkins, and CI/CD pipelines., • Strong knowledge of SQL/NoSQL databases and messaging technologies like Kafka.Responsibilities, • Develop and maintain scalable Java backend applications using Spring Boot and Microservices., • Troubleshoot and resolve production issues in AWS/OpenShift environments., • Perform root cause analysis and implement permanent fixes for production incidents., • Monitor application health, analyze logs, heap dumps, and thread dumps to resolve performance and memory issues., • Manage application certificates and ensure secure deployments., • Collaborate with cross-functional teams in an Agile environment and participate in code reviews and production releases.

Job DescriptionTile :- GCP with angular Required Skills Hand on experience on Angular Strong experience with GCP (BigQuery, Cloud Storage, Dataflow) Advanced SQL expertise (joins, aggregations, window functions, optimization) Experience in data warehousing and data modeling Hands on experience with ETL/ELT pipeline development Experience with real time ingestion (Pub/Sub, streaming pipelines) Programming experience in Python/Java for data processing and automation Understanding of data validation, governance, and security practice The pay range for this role is *- * per annum including any bonuses or variable pay. * also offers benefits like medical, vision, dental, life, disability insurance and paid time off (including holidays, parental leave, and sick leave, as required by law). Ask our recruiters for more details on our Benefits package. The exact offer terms will depend on the skill level, educational qualifications, experience and location of the candidate. * is an Equal Employment Opportunity employer. We promote and support a diverse workforce at all levels of the company. All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, age, national origin, or disability. All applicants will be evaluated solely on the basis of their ability, competence, and performance of the essential functions of their positions with or without reasonable accommodations. Reasonable accommodations also are available in the hiring process for applicants with disabilities. Candidates can request a reasonable accommodation by contacting the company ADA Coordinator at *.

Job DescriptionTitle: Voltage Encryption Engineer Location: Parsippany, NJ (Onsite) Duration: Full-time Salary Range: $100,000-$140,000 per annum Job Description Must Have Technical/Functional Skills • Demonstrated experience in data security / encryption engineering, including substantial hands-on administration experience with OpenText / Micro Focus Voltage SecureData., • Hands-on experience installing, configuring, and administering the Voltage SecureData Appliance (SDA), Management Console, Identity Management, and SecureData Simple API / Web Service., • Strong working knowledge of Format-Preserving Encryption (FPE), Secure Stateless Tokenization (SST), Format-Preserving Hash (FPH), and stateless key management., • Experience protecting PII, PCI, and PHI data at rest, in transit, and in use across cloud (AWS/Azure) and on-premises / mainframe environments., • Proficiency integrating Voltage SecureData with databases (DB2, Oracle, SQL Server), Hadoop / big data platforms, and applications via APIs/SDKs (Java, .NET, C)., • Working knowledge of PCI DSS, GDPR, CCPA, and related data privacy / compliance frameworks as they apply to encryption and tokenization., • Experience with certificate and key lifecycle management, HSM integration (e.g., Entrust nShield, Thales), and FIPS 140-2 / Common Criteria compliant deployments, • Scripting / automation skills (Shell, Python, PowerShell) for policy deployment, monitoring, and operational tasks, • Familiarity with Linux/Unix and Windows server administration, networking, and load balancing for appliance clusters Roles & Responsibilities, • Administer, configure, and maintain the OpenText / Micro Focus Voltage SecureData platform (Appliance, Management Console, and policies) across production and non-production environments, • Implement and manage data-centric encryption and tokenization policies to protect PII, PCI, and PHI data at rest, in transit, and in use., • Partner with infrastructure, cloud, database, and application teams to onboard new applications and data stores onto the encryption platform, • Manage identity, access, and key management configurations, including certificate renewals and HSM integration, • Monitor platform health, performance, and capacity; troubleshoot and resolve incidents related to encryption and tokenization services, • Support audits and compliance assessments (PCI DSS, SOX, GDPR, CCPA) by providing evidence of encryption controls and remediating findings, • Develop and maintain runbooks, SOPs, and configuration/architecture documentation for the Voltage environment, • Apply patches, upgrades, and security hardening to Voltage SecureData components; validate changes in lower environments before production rollout, • Collaborate on disaster recovery and business continuity planning for the encryption platform, • Provide Tier 2/3 support and act as subject matter expert for encryption- and tokenization-related requests from application and business teams.

Job DescriptionJob Title: Java Full Stack Developer (LLM/GenAI) Location: Whippany, NJ (Onsite) Duration: Contract Job Description • We are seeking an experienced AI Java Full Stack Developer with expertise in Java, Spring Boot, Microservices, LLMs, RAG, and AI application development. The ideal candidate will build scalable enterprise applications by integrating Generative AI capabilities into modern Java-based systems.Required Skills, • 7 years of experience in Java Full Stack Development., • Strong experience with Java 8/11/17 , OOP, Spring Boot, Microservices, REST APIs., • Frontend experience with React.js or Angular., • Experience with LLMs, RAG, Prompt Engineering, and AI API integration (OpenAI, Azure OpenAI, Claude, Gemini)., • Hands-on experience with LangChain/LangGraph/LlamaIndex and Vector Databases (Pinecone, FAISS, ChromaDB)., • Knowledge of AI security, including Prompt Injection, Data Leakage, Hallucinations, and OWASP Top 10 for LLMs., • Experience with Git, Jenkins CI/CD, Docker, Kubernetes/OpenShift, and SQL/NoSQL databases., • Strong problem-solving and communication skills.

Job Description Must be Local to New Jersey. Must have Networking/Telecom and Java 21 experience. Must attend one round in-person interview. Java Fullstack Developer Middletown, NJ (Onsite) Long term Contract Client Focus: They look for solid experience and will ask about the projects worked on from both a technical and business perspective. The required experience leans more toward backend than frontend. Fullstack Developer with networking experience preferably at a telecom. Skills: Java (Java 21), Springboot, Javascripts, React, Angular Rest API, PostgreSQL, MySQL.

Job DescriptionJob Title: Android Developer Location: Whippany NJ Duration: Contract • We are looking for an experienced Android Developer to build and maintain high-quality native Android applications.Required Skills:, • Strong Kotlin/Java and Android SDK experience., • Hands-on experience with Jetpack Compose, MVVM, and Clean Architecture., • Experience with ViewModel, LiveData, Room, Retrofit, REST/GraphQL APIs., • Experience with JUnit, Mockito/Espresso for testing., • Knowledge of Jenkins, Gradle, CI/CD, Git, and Agile/Scrum., • Strong debugging, problem-solving, and communication skills.

Job DescriptionAI Engineers - Agentic Development & AI-Augmented Engineering Responsibilities • Design and implement "loop engineering" workflows using Claude Code and similar tools, defining how agents plan, execute, test, and iterate on code changes, • Architect Model Context Protocol (MCP) servers and tool schemas that are legible and safe for LLM agents to use, • Define human-in-the-loop checkpoints, autonomy boundaries, and rollback strategies for agent-driven changes, • Build evaluation harnesses and observability practices to measure agent output quality and catch regressions, • Design and review microservice and microfrontend architecture using C4 diagrams and Domain-Driven Design principles, • Drive test-driven development practices across teams, including contract testing between services, • Own technical decisions across our Java microservices, Node.js services, React/microfrontend UI, and Python tooling, • Design REST APIs and headless component architectures that support both human developers and AI agents, • Establish CI/CD practices that safely incorporate agent-authored pull requests, • Set and enforce security practices for agentic workflows, including prompt injection risk and tool-permission boundaries, • Mentor senior and staff engineers on effective agent-assisted development, • Write RFCs and design docs that translate ambiguous problems into actionable technical plans, documents that both humans and agents can act onRequired Skills & Experience Agentic Development • Hands-on experience with Claude Code or comparable agentic coding tools in production settings, • Strong understanding of MCP (Model Context Protocol) building and consuming MCP servers, • Context engineering: managing context windows, prompt caching, and information architecture for long-running agent sessions, • Awareness of prompt injection and agent-specific security risksArchitecture & Backend, • Deep experience with Java microservices, • Strong REST API design skills, • C4 model architecture documentation and system design, • Domain-Driven Design principles, • Node.js and Python for tooling, services, and automation, • MongoDB schema design, performance, and scaling.Frontend, • ReactJS, headless component architecture, and microfrontend design patternsTesting & Quality, • Test-driven development (TDD) as a core practice, not an afterthought, • Playwright for end-to-end testing, • Contract testing (e.g., Pact) across microservice boundaries

Job Description Job Overview: • A highly skilled Senior Full Stack Developer with 8 12 years of experience in React.js, Java Spring Boot, and Scala., • Proficient in frontend and backend development, microservices, and cloud-native architectures. Strong expertise in functional programming, system design, and scalable distributed systems., • Adept at CI/CD, Agile methodologies, and best software development practices. Responsibilities, Skills, Experience:, • Developing web frontends using React with hands-on experience in React.js., • Proficiency in JavaScript, TypeScript, CSS/SCSS., • Knowledge of key React concepts: Components, State Management, Routing frameworks., • Experience with WebSockets for real-time communication., • Experience with Java Spring-based frameworks & libraries (preferably Spring Boot) for enterprise applications., • Experience with RESTful APIs., • Knowledge of XML, SOAP, JSON, Protobufs, GraphQL., • Proficiency in developing applications and microservices using Scala/Java (minor/knowledge)., • Experience with functional programming such as Scala or Haskell., • Strong understanding of algorithms, data structures, design patterns., • Experience with multi-threading, asynchronous programming, load balancing, resiliency., • Familiarity with front-end and back-end architectures., • Best Practices & Agile Methodologies:, • Familiar with industry best practices for software development., • Agile delivery using Sprint/Kanban., • Test-First development using TDD/BDD., • Integrated telemetry., • Experience working with NoSQL databases such as MongoDB., • Experience with cloud-native, scalable, and highly available distributed systems (Openshift/Kubernetes)., • Experience with CI/CD tooling and automation., • Experience with Git or similar version control systems.

Job Description Job Title: QA Engineer (Karate Automation) Location: Jersey City, NJ (Hybrid/Onsite) Duration: Long-Term Contract Job Description We are seeking an experienced QA Engineer with strong expertise in Karate Automation Testing to join our team. The ideal candidate will be responsible for designing, developing, and executing automated test solutions for API and web applications while ensuring high-quality software delivery. Required Skills: • 5 years of experience in Software Quality Assurance., • Strong hands-on experience with Karate Framework for API automation testing., • Experience in API testing using REST and SOAP services., • Strong knowledge of Java, Maven, and Test Automation frameworks., • Experience with BDD (Behavior-Driven Development) concepts., • Expertise in creating and maintaining automated test scripts., • Experience with Postman, Swagger, and API validation., • Knowledge of SQL and database testing., • Experience with Jenkins, Git, and CI/CD pipelines., • Strong understanding of SDLC, STLC, Agile, and Scrum methodologies., • Excellent debugging, analytical, and problem-solving skills.

Job DescriptionOur mission At Healthpeak, we give our Forward Deployed Software Engineers the autonomy of a startup with the backing, scope, and staying power of a well‑established organization. We exist to transform technology into a revenue‑generating arm of the real estate business, building products and platforms that directly support our tenants, partners, and the teams who serve them every day. We are looking for interns to join us for Summer 2027 ! As an FDSE, you will be part of a small, agile pod and will directly embed with business teams. You will work side‑by‑side with operators, asset managers, and customer‑facing colleagues to rapidly identify opportunities, design solutions, and deliver real value. This is a hands‑on, high‑impact role for engineers who thrive close to users, enjoy ambiguity, and want to see their work make a tangible difference. You will relentlessly prototype, test, launch, and scale new ideas—often moving from concept to production in the matter of weeks. Our first and most important customers are our peers inside Healthpeak, and our ultimate goal is to create delightful, seamless experiences for our tenants and partners by relentlessly minimizing friction. What we’re looking for • Inquisitive engineers who care just as much about why we’re building it as how it should be built. Those who dare to reimagine how work can be done., • Proven programming expertise across languages such as Python, Java, C++, and TypeScript/JavaScript, with hands-on experience developing alongside AI agents (e.g., Claude Code). Backgrounds in Computer Science, Mathematics, Software Engineering, Physics, or Data Science are especially relevant., • Strong technical problem-solving skills, including practical experience with data structures, storage systems, cloud infrastructure, front-end frameworks, and related technologies., • Demonstrated ability to collaborate effectively with both technical and non-technical stakeholders, thriving in fast-paced environments with evolving goals and iterative user feedback., • Self-directed and adaptable learner, capable of working independently and making sound decisions with minimal oversight., • Expected hours: 40 hrs per week over 12 weeks, • Pay rate: $25/hr Powered by JazzHR ss4v1Qi95q

Job Description Job Title: Java Backend Developer Location: Whippany / Wilmington, New Jersey Employment Type: Long-Term Contract Work Setting: Hybrid We are seeking an experienced Java Backend Developer to join a long-term development team in Whippany, NJ. The ideal candidate will have strong hands-on experience with Java, Spring Boot, React, and cloud technologies, particularly OpenShift, along with a solid understanding of the Software Development Life Cycle (SDLC) and software testing. The developer will contribute to application development, enhancement, testing, deployment, and maintenance while collaborating with cross-functional teams throughout the development lifecycle. Key Responsibilities • Design, develop, enhance, and maintain applications using Java., • Develop backend services and applications using Spring Boot., • Contribute to frontend development using React., • Develop and integrate applications using cloud technologies, including OpenShift., • Participate throughout the Software Development Life Cycle (SDLC)., • Analyze requirements and translate them into technical solutions., • Perform unit, integration, and application testing., • Troubleshoot and resolve application issues., • Collaborate with developers, testers, architects, and other stakeholders., • Participate in code reviews and follow development best practices., • Support application deployment and maintenance activities. Required Qualifications, • Strong hands-on experience with Java., • Hands-on experience with Spring Boot., • Experience with React., • Experience with Cloud Technologies, particularly OpenShift., • Strong understanding of SDLC processes., • Experience with software/application testing., • Strong problem-solving and communication skills., • Ability to work effectively in a hybrid environment.

Job DescriptionJob Title: Senior AEM Developer Location: Whippany, NJ (Hybrid) Duration: Contract Job Description: Job Description: • We are seeking a Senior AEM Developer with strong experience in Adobe Experience Manager (AEM), Java, and web technologies. The candidate will design, develop, integrate, and support scalable AEM-based digital solutions.Required Skills:, • Strong experience with Adobe Experience Manager (AEM), • Strong Java/J2EE development experience, • Experience with AEM components, templates, workflows, and OSGi, • Strong knowledge of HTML, CSS, JavaScript, • Experience with REST APIs and web services, • Experience with AEM integrations and troubleshooting, • Good understanding of Agile/Scrum methodology, • Strong problem-solving and communication skills

Job Description We are seeking a highly skilled and experienced Consultant NodeJS with AWS (cloud) to join our team. The ideal candidate will have a minimum of 8 years of professional experience as an UI Developer and experience in Java Backend +Node JS +AWS or Fullstack + Node JS + AWS kind of profiles. As a Consultant NodeJS with AWS (cloud), you will be responsible for developing, implementing, and maintaining software solutions using NodeJS and AWS cloud technologies. You will work on a variety of projects and collaborate with cross-functional teams to design and develop high-quality software solutions that meet the needs of our clients. Essential Skills: • Minimum 8 years of professional experience as an UI Developer, • Strong experience with NodeJS, ReactJS and ExpressJS, • Proficient in programming language: Python or Java, • Experience with other Java technologies such as JSF framework, AJAX, Spring application framework, Hibernate object/relational persistence, JavaScript, HTML 5, and CSS 3, • Unix shell scripting is preferred, • Ability to work in Agile sprint teams, • Strong experience with AWS technologies including AWS CodeBuild, AWS CodeCommit, AWS CodePipeline, AWS Lambda, API Gateway, AWS CLI/Yaml/CloudFormation, and Serverless Deployment If you possess the required skills and experience for this role, we would love to hear from you. We offer a competitive salary, comprehensive benefits package, and opportunities for growth and advancement within our organization. To apply, please submit your resume and cover letter detailing your experience and qualifications for this position.

Job DescriptionTitle: Applied AI Engineer Location: New York City, NY Work Arrangement: Hybrid - 3 days onsite Duration: 12-Month Contract Experience Range: 10 years Our client is seeking an Applied AI Engineer with 10 years of experience to design, build, and operationalize generative AI solutions across their Lending business lines. This role offers the opportunity to architect enterprise-grade GenAI workflows, establish LLMOps best practices, and evolve into a platform owner for shared AI standards. Responsibilities & Qualifications • Design and evolve reusable GenAI workflows and agentic systems deployed across multiple Lending business units, • Develop enterprise-grade AI-powered document ingestion, data extraction, and content generation capabilities, • Build AI assistants embedded in Lending systems using agentic workflows and orchestration patterns, • Deliver automated workflows for content generation, reporting, and approval processes, • Establish and operationalize LLMOps practices including extraction accuracy monitoring, prompt management, and audit controls, • Design and implement security controls for entitlements, PII handling, and governance within AI systems, • Provide expert technical guidance on GenAI architecture, model selection, and platform orchestration decisions, • Act as hands-on technical expert with a clear advancement path to platform owner for enterprise GenAI standards Requirements • 10 years of software engineering experience with demonstrated expertise in generative AI solutions, • Strong proficiency with LangChain, LLM platforms, and RAG (Retrieval-Augmented Generation) architectures, • Production-level experience with Python or Java and building scalable ML systems, • Hands-on expertise in agentic workflows, vector search, prompt management, and data ingestion pipelines, • Deep understanding of LLMOps practices including model monitoring, logging, and production reliability, • Experience designing and implementing data pipelines and working with large language models in enterprise environments, • Strong grasp of AI security, compliance, and governance requirements for financial services or similarly regulated industries

Job Description Title: Full Stack Engineer Location: Delaware, Onsite Duration: 3 Months for Contract Must-have skills: Java, Spring Boot. Candidates should have 8 years of relevant experience. Strong critical thinking and problem-solving skills with clear communication abilities are required. Experience with private and public cloud platforms such as AWS, Google Cloud, and Microsoft Azure is preferred. Experience working in Linux/Unix environments is preferred. Experience with Terraform is preferred. Job description: Design and build scalable applications using Java and Spring Boot. Develop responsive frontend interfaces using React. Implement and integrate business workflows using Camunda. Build and maintain RESTful APIs and microservices. Ensure code quality through unit, integration, and end-to-end testing. Create UI test automation using Cypress. Perform performance and load testing using JMeter. Collaborate with cross-functional teams in Agile environments. Optimize application performance, scalability, and reliability.

Job DescriptionJob Title: UI/UX Engineer Location: Whippany, NJ (Hybrid) Duration: Contract Job Description • We are seeking a UI/UX Engineer with strong experience in website development using JavaScript/React.js along with iOS or Android application development. The ideal candidate will build intuitive, responsive, and high-quality user experiences across web and mobile platforms.Required Skills:, • Strong experience with JavaScript, React.js, HTML5, and CSS3, • Hands-on experience in iOS (Swift) or Android (Kotlin/Java) development, • Knowledge of responsive UI design and UX best practices, • Experience integrating REST APIs, • Familiarity with Git and Agile methodologiesResponsibilities:, • Develop responsive web applications using React.js., • Build and maintain iOS or Android mobile applications., • Collaborate with UX designers and backend developers., • Optimize application performance and ensure a seamless user experience across web and mobile platforms.

Job Description Job Title: API SDET Location: Whippany, NJ (Hybrid) Requirement: 1 Position (Urgent) We are looking for an experienced API SDET for an urgent hybrid opportunity in Whippany, NJ. Key Requirement: • Strong Java programming skills are mandatory., • This is a Hybrid Test Development role with a primary focus on Java development. Work Location: Whippany, NJ (Hybrid) If you have suitable candidates available immediately, please share their updated resume along with visa status, current location, and contact details.

Job Description Position: junior software engineer Onsite: 5 days onsite Clearance: Must have an active Top Secret Location: El Segundo, CA or Albuquerque, New Mexico Interview process: 1 video interview to hire Contract: 6-12 months extension (they would like to bring someone on perm) Must have: Java or Python or C (if they have all three, would be perfect), REST API development, CI/CD Nice to have: Space or mission systems, or ground systems experience · Active TS Clearance (TS/SCI preferred) · Strong software engineering fundamentals · Backend development experience · Java, C , Python, or JavaScript · REST API development · Object-oriented programming · CI/CD, DevSecOps, Agile · Space, mission systems, or ground systems experience

Job DescriptionFront Office QA Engineer - Python Programmer - Charlotte, NC - Contract - $54-64 Per HR Designs, codes, and maintains software applications to meet user needs in a hybrid work environment. This contract position requires collaboration with developers and stakeholders to develop application features and fix bugs using a variety of programming languages and development frameworks. Key Responsibilities • Design application architecture to meet user requirements., • Code and test software applications for functionality and efficiency., • Fix bugs and optimize application performance., • Collaborate with other developers and stakeholders to enhance application features., • Maintain application documentation and version control., • Must have extensive Fixed Income Capital Markets expertise.Qualifications, • Proficiency in programming languages such as Java, C#, or Python., • Experience with development frameworks., • Strong problem-solving and analytical skills., • Ability to work collaboratively in a team environment., • Excellent communication skills.Core Technologies Java | C# | Python | Development Frameworks Contact Authorization By applying for this job, you agree to receive AI-generated calls, text messages, and/or emails from Mitchell Martin Inc and its affiliates and contracted partners at various frequency through traditional and automated methods. Message and data rates may apply for texts. Carriers are not liable for delayed or undelivered messages. You can access our privacy policy here (https://www.mitchellmartin.com/privacy-policy). Benefits Learn more about our benefits offerings here (https://www.mitchellmartin.com/careers/benefits-perks) Onboarding Expectations Learn more about our Onboarding Process here (https://youtu.be/rjV_NFYjyY4) EEO Statement Learn more about our EEO policy here (https://www.mitchellmartin.com/eoe-statement) #LI-AA2