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machine learning infrastructure engineer
Boeing
Chief Engineer, Artificial Intelligence and Autonomy
Boeing El Segundo, California
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. At Boeing's Space Mission Systems, we innovate and collaborate to advance connectivity for a better world. We are committed to fostering an environment for every teammate that is welcoming, respectful, and inclusive, with exceptional opportunity for professional growth. Find your future with us. SMS is seeking a Chief Engineer, Artificial Intelligence and Autonomy to lead the establishment, growth, and operational maturation of the enterprise AI function across the full portfolio of SMS programs in Seal Beach or El Segundo, CA. This is a newly created management position responsible for increasing the adoption and integration of AI capabilities throughout SMS engineering programs, manufacturing operations, and flight systems. This Chief Engineer will define and execute the Company's AI strategy across strategic domains including manufacturing intelligence, constellation autonomy, spectrum orchestration, and AI-assisted engineering. The role reports to Engineering VP and Space Missions Systems Chief Engineer, with a dotted-line report to the VP of Program Management and cross-functional authority across Engineering, Flight Operations, and Manufacturing. Position Responsibilities: Enterprise AI Strategy & Program Coordination: Develop and maintain a comprehensive enterprise AI strategy that increases the use of AI across the full portfolio of SMS programs, serving as the primary coordinator between programs and engineering leadership Define and present the enterprise AI roadmap to Segment Leadership, the VP of Program Management, and the executive leadership team, including business case definition, value propositions, technology readiness level (TRL) reduction plans, and program on-ramp strategies for AI-assisted engineering and space edge compute Coordinate between SMS programs and engineering organizations on the adoption and deployment of AI-assisted coding tools and autonomous software agents to accelerate development velocity and reduce engineering cycle times Identify, evaluate, and manage strategic AI partnerships, vendor relationships, and technology acquisitions that accelerate the Company's AI capabilities Mature and facilitate the intake, qualification, and prioritization of AI, analytics, and automation projects across programs, ensuring the right problems are addressed with executive sponsorship Organizational Design & Team Building: Establish the AI & Autonomy function as a new organizational capability from the ground up, defining structure, operating model, and governance Recruit, hire, and lead a cross-functional AI team spanning AI/ML engineers, data engineers, data scientists, MLOps engineers, and domain specialists Build and manage an independent AI budget, compute infrastructure (GPU clusters), tooling, and vendor partnerships AI-Assisted Engineering & Autonomous Agents: Drive the adoption of AI-assisted coding and autonomous agents across SMS engineering programs, enabling engineers to leverage generative AI, code copilots, and agentic workflows for design, analysis, and verification tasks Develop the business strategy, TRL reduction roadmap, and program on-ramp plans for integrating AI into engineering workflows and space edge compute flight systems, from concept through flight qualification and operational deployment Facilitate discovery workshops with engineering and program leaders to define problems, quantify value, and scope AI solutions across the portfolio Factory AI Automation & Manufacturing Intelligence: Lead development and deployment of AI automation for factory processes, including photographic and computer vision-based quality inspections of satellite components and assemblies Implement AI-driven engineering buy-off automation, accelerating verification and validation across integration and test workflows through autonomous review and decision support Deploy autonomous research capabilities enabling AI-assisted document analysis, anomaly flagging, and compliance verification across satellite build records and End Item Data Packages (EIDPs) Deliver a fully integrated Factory Product Assurance Automation Platform supporting satellite production at scale Flight Edge Computing & Machine Learning: Create and own the business strategy, TRL reduction plan, and technology maturation roadmap for AI-assisted engineering of space edge compute systems, flight inference processors, and onboard machine learning architectures-from early concept through flight qualification and operational deployment Define hardware architecture for space edge compute, onboard storage, and flight inference systems, enabling AI-driven data store-and-forward, real-time ML inference, and autonomous decision-making capabilities on operational satellites Develop and deploy ML models for constellation scheduling optimization, including beam allocation, power management, thermal budget optimization, and coverage planning Close the sim-to-reality gap by using on-orbit performance truth data to continuously improve predictive models and feed insights back into factory integration and test procedures Spectrum Orchestration & Autonomous Operations: Develop and deploy AI-driven dynamic interference mapping and avoidance protocols across the constellation's operating spectrum, leveraging physics-informed models validated against on-orbit telemetry Build AI-optimized beam-hopping and resource scheduling systems that dynamically allocate spectrum and power resources based on real-time demand, interference conditions, and orbital geometry Deliver the integrated Spectrum Allocation Orchestration Platform as an operational system managing dynamic spectrum access across the commercial constellation Cross-Functional Integration & Stakeholder Engagement: Operate with cross-functional authority across Engineering, Flight Operations, Manufacturing, and Product to embed AI into existing workflows, coordinating with the VP of Program Management to align AI initiatives with program schedules and milestones Establish standing technical syncs with Engineering, Flight Operations, and Manufacturing leadership to ensure AI initiatives are validated against domain expertise before deployment Lead stakeholder communications covering AI strategies, program status, and value delivery across SMS leadership and program teams Create materials and media to convey AI strategies and product value, including presentations, demonstrations, visual diagrams, and technical briefings Position AI as an amplifier of existing engineering capabilities-not a replacement-ensuring adoption is collaborative and trust-based across the organization Basic Qualifications (Required Skills/Experience): Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement 5+ years of experience building and leading artificial intelligence/machine learning organizations from inception, including hiring, budgeting, infrastructure provisioning, and delivery of production machine learning systems Experience with cross-functional leadership working with different organizations and operations teams Experience developing artificial intelligence/machine learning strategies including business case development, TRL (Technology Readiness Level) assessment, and technology transition planning Preferred Qualifications (Desired Skills/Experience): Active TS/SCI clearance 10+ years of experience collaborating with and influencing senior management and executive leadership across engineering, operations, and program management functions Experience with physics-informed machine learning, custom ML models for hardware systems, and AI deployment in safety-critical or mission-critical environments Experience with satellite communications, phased array antenna systems, digital beamforming, or comparable complex RF/signal processing systems Bachelor's degree or higher in Computer Science, Electrical Engineering, Aerospace Engineering, or a related technical field Excellent stakeholder management skills including the ability to communicate with and influence people from varying backgrounds, including members of senior leadership teams Experience in aerospace and defense satellite programs (constellation management, payload engineering, launch operations) Experience with AI-assisted software development tools, autonomous coding agents, and agentic AI workflows in engineering environments Experience with manufacturing AI including computer vision quality inspection, predictive maintenance, and factory digital twins Background in space edge computing, flight inference systems, onboard ML, and flight computer architectures for space applications, including TRL maturation of compute hardware Experience with ASIC/custom silicon architectures and understanding of how DSP hardware intersects with ML inference workloads . click apply for full job details
04/06/2026
Full time
Job Description At Boeing, we innovate and collaborate to make the world a better place. We're committed to fostering an environment for every teammate that's welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us. At Boeing's Space Mission Systems, we innovate and collaborate to advance connectivity for a better world. We are committed to fostering an environment for every teammate that is welcoming, respectful, and inclusive, with exceptional opportunity for professional growth. Find your future with us. SMS is seeking a Chief Engineer, Artificial Intelligence and Autonomy to lead the establishment, growth, and operational maturation of the enterprise AI function across the full portfolio of SMS programs in Seal Beach or El Segundo, CA. This is a newly created management position responsible for increasing the adoption and integration of AI capabilities throughout SMS engineering programs, manufacturing operations, and flight systems. This Chief Engineer will define and execute the Company's AI strategy across strategic domains including manufacturing intelligence, constellation autonomy, spectrum orchestration, and AI-assisted engineering. The role reports to Engineering VP and Space Missions Systems Chief Engineer, with a dotted-line report to the VP of Program Management and cross-functional authority across Engineering, Flight Operations, and Manufacturing. Position Responsibilities: Enterprise AI Strategy & Program Coordination: Develop and maintain a comprehensive enterprise AI strategy that increases the use of AI across the full portfolio of SMS programs, serving as the primary coordinator between programs and engineering leadership Define and present the enterprise AI roadmap to Segment Leadership, the VP of Program Management, and the executive leadership team, including business case definition, value propositions, technology readiness level (TRL) reduction plans, and program on-ramp strategies for AI-assisted engineering and space edge compute Coordinate between SMS programs and engineering organizations on the adoption and deployment of AI-assisted coding tools and autonomous software agents to accelerate development velocity and reduce engineering cycle times Identify, evaluate, and manage strategic AI partnerships, vendor relationships, and technology acquisitions that accelerate the Company's AI capabilities Mature and facilitate the intake, qualification, and prioritization of AI, analytics, and automation projects across programs, ensuring the right problems are addressed with executive sponsorship Organizational Design & Team Building: Establish the AI & Autonomy function as a new organizational capability from the ground up, defining structure, operating model, and governance Recruit, hire, and lead a cross-functional AI team spanning AI/ML engineers, data engineers, data scientists, MLOps engineers, and domain specialists Build and manage an independent AI budget, compute infrastructure (GPU clusters), tooling, and vendor partnerships AI-Assisted Engineering & Autonomous Agents: Drive the adoption of AI-assisted coding and autonomous agents across SMS engineering programs, enabling engineers to leverage generative AI, code copilots, and agentic workflows for design, analysis, and verification tasks Develop the business strategy, TRL reduction roadmap, and program on-ramp plans for integrating AI into engineering workflows and space edge compute flight systems, from concept through flight qualification and operational deployment Facilitate discovery workshops with engineering and program leaders to define problems, quantify value, and scope AI solutions across the portfolio Factory AI Automation & Manufacturing Intelligence: Lead development and deployment of AI automation for factory processes, including photographic and computer vision-based quality inspections of satellite components and assemblies Implement AI-driven engineering buy-off automation, accelerating verification and validation across integration and test workflows through autonomous review and decision support Deploy autonomous research capabilities enabling AI-assisted document analysis, anomaly flagging, and compliance verification across satellite build records and End Item Data Packages (EIDPs) Deliver a fully integrated Factory Product Assurance Automation Platform supporting satellite production at scale Flight Edge Computing & Machine Learning: Create and own the business strategy, TRL reduction plan, and technology maturation roadmap for AI-assisted engineering of space edge compute systems, flight inference processors, and onboard machine learning architectures-from early concept through flight qualification and operational deployment Define hardware architecture for space edge compute, onboard storage, and flight inference systems, enabling AI-driven data store-and-forward, real-time ML inference, and autonomous decision-making capabilities on operational satellites Develop and deploy ML models for constellation scheduling optimization, including beam allocation, power management, thermal budget optimization, and coverage planning Close the sim-to-reality gap by using on-orbit performance truth data to continuously improve predictive models and feed insights back into factory integration and test procedures Spectrum Orchestration & Autonomous Operations: Develop and deploy AI-driven dynamic interference mapping and avoidance protocols across the constellation's operating spectrum, leveraging physics-informed models validated against on-orbit telemetry Build AI-optimized beam-hopping and resource scheduling systems that dynamically allocate spectrum and power resources based on real-time demand, interference conditions, and orbital geometry Deliver the integrated Spectrum Allocation Orchestration Platform as an operational system managing dynamic spectrum access across the commercial constellation Cross-Functional Integration & Stakeholder Engagement: Operate with cross-functional authority across Engineering, Flight Operations, Manufacturing, and Product to embed AI into existing workflows, coordinating with the VP of Program Management to align AI initiatives with program schedules and milestones Establish standing technical syncs with Engineering, Flight Operations, and Manufacturing leadership to ensure AI initiatives are validated against domain expertise before deployment Lead stakeholder communications covering AI strategies, program status, and value delivery across SMS leadership and program teams Create materials and media to convey AI strategies and product value, including presentations, demonstrations, visual diagrams, and technical briefings Position AI as an amplifier of existing engineering capabilities-not a replacement-ensuring adoption is collaborative and trust-based across the organization Basic Qualifications (Required Skills/Experience): Bachelor of Science degree in Engineering, Engineering Technology (including Manufacturing Technology), Computer Science, Data Science, Mathematics, Physics, Chemistry or non-US equivalent qualifications directly related to the work statement 5+ years of experience building and leading artificial intelligence/machine learning organizations from inception, including hiring, budgeting, infrastructure provisioning, and delivery of production machine learning systems Experience with cross-functional leadership working with different organizations and operations teams Experience developing artificial intelligence/machine learning strategies including business case development, TRL (Technology Readiness Level) assessment, and technology transition planning Preferred Qualifications (Desired Skills/Experience): Active TS/SCI clearance 10+ years of experience collaborating with and influencing senior management and executive leadership across engineering, operations, and program management functions Experience with physics-informed machine learning, custom ML models for hardware systems, and AI deployment in safety-critical or mission-critical environments Experience with satellite communications, phased array antenna systems, digital beamforming, or comparable complex RF/signal processing systems Bachelor's degree or higher in Computer Science, Electrical Engineering, Aerospace Engineering, or a related technical field Excellent stakeholder management skills including the ability to communicate with and influence people from varying backgrounds, including members of senior leadership teams Experience in aerospace and defense satellite programs (constellation management, payload engineering, launch operations) Experience with AI-assisted software development tools, autonomous coding agents, and agentic AI workflows in engineering environments Experience with manufacturing AI including computer vision quality inspection, predictive maintenance, and factory digital twins Background in space edge computing, flight inference systems, onboard ML, and flight computer architectures for space applications, including TRL maturation of compute hardware Experience with ASIC/custom silicon architectures and understanding of how DSP hardware intersects with ML inference workloads . click apply for full job details
Senior Data Scientist Machine Learning Operations Gen AI - Remote
Sentara Health Virginia Beach, Virginia
City/State Virginia Beach, VA Work Shift First (Days) Overview: Sentara is hiring for a Senior Data Scientist! This position is fully remote. Overview We are seeking a highly skilled and experienced Data Science ML Operations and Gen AI Engineer (or Senior) to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better healthcare. The Senior Data Scientist will leverage data to improve healthcare outcomes and drive data-driven decision-making. Leveraging expertise in statistical analysis and machine learning, this role will collaborate with cross-functional teams to solve complex healthcare challenges and enhance patient care. This role will directly contribute to advancing medical research, optimizing healthcare processes, and delivering innovative solutions in the healthcare industry. As a Senior ML Engineer on our team, you will play a crucial role in identifying gaps in our existing ML platform and architecting and building solutions to address those gaps. You will also collaborate with the AI team's ML Scientists and our partner data engineering and software development teams to bring ML AND Gen AI models to production and maintain their health and integrity while in production. Your expertise in machine learning and Gen AI, coupled with a strong background in software development, will be instrumental in driving the success of Sentara's AI/ML initiatives. Qualifications: • 5+ years building production software/ML systems, including 1+ years of experience with LLMs/GenAI. • Proficient in Python and one major DL/LLM stack (e.g., PyTorch/Transformers); experience with LangChain/LlamaIndex, vector DBs, and cloud (AWS/Azure/GCP). • Demonstrated delivery of RAG, prompt engineering, evaluation frameworks, and guardrails in production. • Strength in APIs, distributed systems, and ML Ops (K8s, CI/CD, monitoring). • Experience with EPIC health platform is highly preferred • Experience with ML platforms and ML Ops: Demonstrated experience in assessing and improving ML platforms, identifying gaps, and architecting solutions to address them. Strong familiarity with ML platform components such as data ingestion, preprocessing, feature stores, model training, deployment, and monitoring. • Experience with SQL and big data platforms such as Postgres, Redshift and Snowflake • Experience with Agile/Scrum methodology and best practices Preferred: • Previous work experience with Generative AI and ML Ops in healthcare EPIC environment • Understanding of use and implementation of Vector Databases • Kubernetes container orchestration experience Responsibilities • Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions • Lead hands-on delivery of scalable GenAI solutions from problem framing prototyping evaluation production monitoring. • Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation). • Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering. • Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls. • ML platform and ML Ops: Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem. Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement. Develop tools and solutions that help the team build, deploy, and monitor AI/ML solutions efficiently. • System scalability and reliability: Optimize the scalability, performance, and reliability and AI Team solutions by implementing best practices and leveraging industry-standard technologies. Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions. Design scalable and efficient systems that leverage the power of machine learning for enhanced performance and capabilities. • Data processing and workflow pipelines: Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency. Work with data engineering and data platform teams to design and implement robust data pipelines that support the AI team's needs. • Model deployment and monitoring: Evaluate and optimize model prototypes for real-world performance. Work with infrastructure and development teams to integrate ML models into production systems. Work closely with partner teams to communicate and understand technical requirements and challenges. • As part of Sentara's Data Science team you will be responsible for implementation and operationalization of AI/ML models. You will work with other machine learning engineers, data scientists, software engineers and platform engineers to ensure success of the AI/ML implementations. Specific responsibilities will include: • Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. • Take offline models data scientists build and turn them into a real machine learning production system. Education Bachelor's Degree (Required) Certification/Licensure No specific certification or licensure requirements Experience Required to have 5+ years of experience as a Data Scientist with a strong focus on Azure and Microsoft Data Science, AI, and machine learning toolsets. Required to have strong problem-solving skills and the ability to tackle complex healthcare challenges using data-driven approaches. Can help the Data Science infrastructure building up, working with ML Ops team for model implementation, mentoring and developing junior staff. Required to have s trong proficiency in data analysis, data manipulation, and data visualization using Python. Required to have f amiliarity with healthcare-related datasets, medical terminologies, and electronic health records (EHR) data. Required to have knowledge of statistical techniques, hypothesis testing, and experimental design for healthcare research. Required to have s trong machine learning expertise: Proficient in machine learning algorithms, statistical modeling, and data analysis. Hands-on experience with standard ML frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, XGBoost, TensorFlow, or Keras). Required to have solid understanding of data engineering principles, data structures, and algorithms. Proficient in Python and/or other programming languages commonly used in ML development. Required to have experience in technologies, frameworks and architecture like Java or Python, Angular, React, JSON, Application Servers, CI/CD is preferred. Required to have experience with one or more AI automations platforms like Kubeflow pipeline, MLFlow, Azure Pipeline, AWS Sage Maker Pipeline, Airflow, Jenkins, Spark, Hadoop, Kafka, Jira and GIT. We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for full-time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan •Colleagues have the opportunity to earn an annual discretionary bonus ifestablished system and employee eligibility criteria is met. Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves. In support of our mission "to improve health every day," this is a tobacco-free environment. For positions that are available as remote work, Sentara Health employs associates in the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
04/06/2026
Full time
City/State Virginia Beach, VA Work Shift First (Days) Overview: Sentara is hiring for a Senior Data Scientist! This position is fully remote. Overview We are seeking a highly skilled and experienced Data Science ML Operations and Gen AI Engineer (or Senior) to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better healthcare. The Senior Data Scientist will leverage data to improve healthcare outcomes and drive data-driven decision-making. Leveraging expertise in statistical analysis and machine learning, this role will collaborate with cross-functional teams to solve complex healthcare challenges and enhance patient care. This role will directly contribute to advancing medical research, optimizing healthcare processes, and delivering innovative solutions in the healthcare industry. As a Senior ML Engineer on our team, you will play a crucial role in identifying gaps in our existing ML platform and architecting and building solutions to address those gaps. You will also collaborate with the AI team's ML Scientists and our partner data engineering and software development teams to bring ML AND Gen AI models to production and maintain their health and integrity while in production. Your expertise in machine learning and Gen AI, coupled with a strong background in software development, will be instrumental in driving the success of Sentara's AI/ML initiatives. Qualifications: • 5+ years building production software/ML systems, including 1+ years of experience with LLMs/GenAI. • Proficient in Python and one major DL/LLM stack (e.g., PyTorch/Transformers); experience with LangChain/LlamaIndex, vector DBs, and cloud (AWS/Azure/GCP). • Demonstrated delivery of RAG, prompt engineering, evaluation frameworks, and guardrails in production. • Strength in APIs, distributed systems, and ML Ops (K8s, CI/CD, monitoring). • Experience with EPIC health platform is highly preferred • Experience with ML platforms and ML Ops: Demonstrated experience in assessing and improving ML platforms, identifying gaps, and architecting solutions to address them. Strong familiarity with ML platform components such as data ingestion, preprocessing, feature stores, model training, deployment, and monitoring. • Experience with SQL and big data platforms such as Postgres, Redshift and Snowflake • Experience with Agile/Scrum methodology and best practices Preferred: • Previous work experience with Generative AI and ML Ops in healthcare EPIC environment • Understanding of use and implementation of Vector Databases • Kubernetes container orchestration experience Responsibilities • Responsible for design and development of production-grade Machine Learning ops and Gen AI solutions • Lead hands-on delivery of scalable GenAI solutions from problem framing prototyping evaluation production monitoring. • Build internal copilots/assistants (knowledge search, code/content generation) and client-facing products (conversational analytics, summarization, recommendations, workflow automation). • Design RAG pipelines, embedding strategies, vector search, and model orchestration; evaluate fine-tuning vs. prompt engineering. • Implement guardrails, safety filters, prompt/version management, latency/throughput optimizations, and cost controls. • ML platform and ML Ops: Identify areas that require improvements or additional functionalities and use your expertise in machine learning and software engineering to architect and develop solutions that fill gaps in our ML platform and development ecosystem. Analyze system performance, scalability, and reliability to pinpoint opportunities for enhancement. Develop tools and solutions that help the team build, deploy, and monitor AI/ML solutions efficiently. • System scalability and reliability: Optimize the scalability, performance, and reliability and AI Team solutions by implementing best practices and leveraging industry-standard technologies. Collaborate with infrastructure teams to ensure smooth integration and deployment of ML solutions. Design scalable and efficient systems that leverage the power of machine learning for enhanced performance and capabilities. • Data processing and workflow pipelines: Streamline data ingestion, preprocessing, feature engineering, and model training workflows to improve efficiency and reduce latency. Work with data engineering and data platform teams to design and implement robust data pipelines that support the AI team's needs. • Model deployment and monitoring: Evaluate and optimize model prototypes for real-world performance. Work with infrastructure and development teams to integrate ML models into production systems. Work closely with partner teams to communicate and understand technical requirements and challenges. • As part of Sentara's Data Science team you will be responsible for implementation and operationalization of AI/ML models. You will work with other machine learning engineers, data scientists, software engineers and platform engineers to ensure success of the AI/ML implementations. Specific responsibilities will include: • Apply software engineering rigor and best practices to machine learning, including AI/MLOPs, CI/CD, automation, etc. • Take offline models data scientists build and turn them into a real machine learning production system. Education Bachelor's Degree (Required) Certification/Licensure No specific certification or licensure requirements Experience Required to have 5+ years of experience as a Data Scientist with a strong focus on Azure and Microsoft Data Science, AI, and machine learning toolsets. Required to have strong problem-solving skills and the ability to tackle complex healthcare challenges using data-driven approaches. Can help the Data Science infrastructure building up, working with ML Ops team for model implementation, mentoring and developing junior staff. Required to have s trong proficiency in data analysis, data manipulation, and data visualization using Python. Required to have f amiliarity with healthcare-related datasets, medical terminologies, and electronic health records (EHR) data. Required to have knowledge of statistical techniques, hypothesis testing, and experimental design for healthcare research. Required to have s trong machine learning expertise: Proficient in machine learning algorithms, statistical modeling, and data analysis. Hands-on experience with standard ML frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, XGBoost, TensorFlow, or Keras). Required to have solid understanding of data engineering principles, data structures, and algorithms. Proficient in Python and/or other programming languages commonly used in ML development. Required to have experience in technologies, frameworks and architecture like Java or Python, Angular, React, JSON, Application Servers, CI/CD is preferred. Required to have experience with one or more AI automations platforms like Kubeflow pipeline, MLFlow, Azure Pipeline, AWS Sage Maker Pipeline, Airflow, Jenkins, Spark, Hadoop, Kafka, Jira and GIT. We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for full-time employment is: $91,416.00 - $152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities. Benefits: Caring For Your Family and Your Career • Medical, Dental, Vision plans • Adoption, Fertility and Surrogacy Reimbursement up to $10,000 • Paid Time Off and Sick Leave • Paid Parental & Family Caregiver Leave • Emergency Backup Care • Long-Term, Short-Term Disability, and Critical Illness plans • Life Insurance • 401k/403B with Employer Match • Tuition Assistance - $5,250/year and discounted educational opportunities through Guild Education • Student Debt Pay Down - $10,000 • Reimbursement for certifications and free access to complete CEUs and professional development •Pet Insurance •Legal Resources Plan •Colleagues have the opportunity to earn an annual discretionary bonus ifestablished system and employee eligibility criteria is met. Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves. In support of our mission "to improve health every day," this is a tobacco-free environment. For positions that are available as remote work, Sentara Health employs associates in the following states: Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.
Senior Data Scientist
Takeda Pharmaceutical Cambridge, Massachusetts
By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description Pursuant to Section 20 C.F.R. 656.10, you are hereby notified that an application for Alien Employment Certification will be filed by Takeda Development Center Americas, Inc. for the following job opportunity: JOB LOCATION: Cambridge, MA POSITION: Senior Data Scientist POSITION DESCRIPTION: Takeda Development Center Americas, Inc. is seeking a Senior Data Scientist with the following duties: collaborate with a diverse set of users and partners across multiple functions to translate unstructured, complex business problems into appropriate data, modelling and analytical solutions; lead data science projects through the data, analytics & machine learning lifecycle; clearly and objectively communicate results, as well as their associated limitations; apply and maintain methods, techniques and developments in analytics and data science; mentor and support other data scientists across multiple projects to drive the development of data science as a capability; develop and review working practices to ensure that data science work is delivered to robust quality standards. Up to 25% domestic travel required for hybrid requirements for onsite meetings and department events. Up to 75% remote work allowed. The estimated salary range reflects an anticipated range for this position. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location. U.S. based employees may be eligible for short-term and/or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation. REQUIREMENTS: Master's degree in Data Science, Analytics, Business Analytics, Computer Science, Engineering, or related field plus 4 years of related experience. Prior experience must include: 4 years of data and analytics experience in life science, pharma, biotech, technology companies or relevant regulated industries; collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions; perform end-to-end data processing including extraction, cleaning, transformation, and analysis using SQL queries across multiple database systems; develop advanced analytical solutions leveraging Python, R, and other programming languages to support data-driven decision making; implement version control practices using Git to manage code repositories and leverage cloud computing infrastructure like AWS; design and implement data visualization solutions using tools like Tableau, Power BI, or similar platforms and enable self-service analytics; present data-driven insights and recommendations to senior leadership and key stakeholders. Full time. $162,000 to $260,000 per year. Qualified applicants can apply at . Please reference job . EOE Any individual may provide documentary evidence bearing on this application, with information on available workers and information on wages and working conditions, to the Certifying Officer, U.S. Department of Labor, Employment and Training Administration, Office of Foreign Labor Certification, 200 Constitution Avenue, NW, Room N-5311, Washington, DC 20210. LocationsBoston, MAWorker TypeEmployeeWorker Sub-TypeRegularTime TypeFull time
04/06/2026
Full time
By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description Pursuant to Section 20 C.F.R. 656.10, you are hereby notified that an application for Alien Employment Certification will be filed by Takeda Development Center Americas, Inc. for the following job opportunity: JOB LOCATION: Cambridge, MA POSITION: Senior Data Scientist POSITION DESCRIPTION: Takeda Development Center Americas, Inc. is seeking a Senior Data Scientist with the following duties: collaborate with a diverse set of users and partners across multiple functions to translate unstructured, complex business problems into appropriate data, modelling and analytical solutions; lead data science projects through the data, analytics & machine learning lifecycle; clearly and objectively communicate results, as well as their associated limitations; apply and maintain methods, techniques and developments in analytics and data science; mentor and support other data scientists across multiple projects to drive the development of data science as a capability; develop and review working practices to ensure that data science work is delivered to robust quality standards. Up to 25% domestic travel required for hybrid requirements for onsite meetings and department events. Up to 75% remote work allowed. The estimated salary range reflects an anticipated range for this position. The actual base salary offered will be in accordance with state or local minimum wage requirements for the job location. U.S. based employees may be eligible for short-term and/or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation. REQUIREMENTS: Master's degree in Data Science, Analytics, Business Analytics, Computer Science, Engineering, or related field plus 4 years of related experience. Prior experience must include: 4 years of data and analytics experience in life science, pharma, biotech, technology companies or relevant regulated industries; collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions; perform end-to-end data processing including extraction, cleaning, transformation, and analysis using SQL queries across multiple database systems; develop advanced analytical solutions leveraging Python, R, and other programming languages to support data-driven decision making; implement version control practices using Git to manage code repositories and leverage cloud computing infrastructure like AWS; design and implement data visualization solutions using tools like Tableau, Power BI, or similar platforms and enable self-service analytics; present data-driven insights and recommendations to senior leadership and key stakeholders. Full time. $162,000 to $260,000 per year. Qualified applicants can apply at . Please reference job . EOE Any individual may provide documentary evidence bearing on this application, with information on available workers and information on wages and working conditions, to the Certifying Officer, U.S. Department of Labor, Employment and Training Administration, Office of Foreign Labor Certification, 200 Constitution Avenue, NW, Room N-5311, Washington, DC 20210. LocationsBoston, MAWorker TypeEmployeeWorker Sub-TypeRegularTime TypeFull time
Senior Manufacturing Test Development Engineer
JABIL CIRCUIT, INC Austin, Texas
Location/Division Specific Information - Austin, TX/ USA - Remote This position supports hybrid work schedule depending on organization needs. How will you make an impact? - Jabil is seeking a Sr. Software Test Development Engineer who will directly contribute to the transformative growth within our Enterprise and Infrastructure division by applying unique and innovative approaches to solving problems within a large-scale software production environment. The Software Test Development Engineer play a vital role in ensuring the quality and reliability of hardware products, contributing to the overall success of the manufacturing process and customer satisfaction. You will be responsible for contributing to the end-to-end architecture, definition, development and production deployment of production software applications and infrastructure spanning multiple customers and manufacturing regions. You will also be responsible for interfacing with internal engineering, manufacturing and quality teams and our end customers to ensure your software deliverables meet the rigorous standards of Jabil's world-class manufacturing environments. What will you do? - Test System Development: Design and develop test systems and procedures for manufacturing processes. This includes creating test plans, test cases, and test scripts to assess the functionality and performance of hardware components or devices such as motherboard, memory, CPU, storage (SSD, HDD, NVMe) and PCIE devices (NIC, GPU, Mezz cards, RAID cards) Test Software Development: Create, validate, release, and maintain test software and scripts that automate the testing process. This software may include code for controlling test equipment, collecting and analyzing data, and generating test reports Test Sustaining: Support and maintenance for the manufacturing server (L10) and rack (L11) level test software and infrastructure deployed at our production facilities, including the implementation of minor system configuration changes (new IPNs) Documentation: Maintain comprehensive manufacturing server (L10) and rack (L11) documentation of test procedures, specifications, and Infrastructure Collaboration: Work closely with cross-functional teams, including hardware engineers, manufacturing engineers, and quality assurance personnel, to ensure alignment on testing requirements and quality standards Continuous Learning: Stay updated on the latest advancements in testing technologies, methodologies, and industry best practices to keep manufacturing processes competitive and up to date Definition and collaboration on overall test infrastructure and application architectures How will you get here? - Education: BS degree in Electrical/Computer Engineering, Computer Science or related field is required Experience: 5-8 years' experience in a software manufacturing test development/sustaining with enterprise server, storage or networking products is required 10+ years of relevant experience in a software manufacturing test development/ sustaining with enterprise server, storage or networking products and some college coursework in lieu of a 4- yr. degree, will be considered Excellent verbal and written communication skills is required Knowledge, Skills, Abilities: Expertise in the following programming/scripting languages: Python, Java, BASH. C, C++, experience a plus Linux development expertise with a solid understanding of its fundamentals: CentOS/Ubuntu Expertise with hardware and API solutions for controlling, managing and stressing L10 devices (servers, network and storage SSDs, NVMe): IPMI, Redfish, mprime, FIO, Linpack, ptugen, memtester Expertise in the creation and configuration (DHCP, PXE boot, nginx) of Virtual Machines (VMs) using VMWare Expertise with leading edge networking systems, hardware, software and protocols including but not limited to enterprise ethernet datacenter switching/routing L1, L2, and L3 (BGP, DHCP Relay, ECMP). Arista CloudVision is a plus Experience with code versioning tools (Git preferred) Strong knowledge of professional software engineering practices for the complete software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations Ability to travel up to 10% globally as required Preferred Qualifications: MS preferred Experience working in a multi-site and multi-cultural environments is a plus
04/06/2026
Full time
Location/Division Specific Information - Austin, TX/ USA - Remote This position supports hybrid work schedule depending on organization needs. How will you make an impact? - Jabil is seeking a Sr. Software Test Development Engineer who will directly contribute to the transformative growth within our Enterprise and Infrastructure division by applying unique and innovative approaches to solving problems within a large-scale software production environment. The Software Test Development Engineer play a vital role in ensuring the quality and reliability of hardware products, contributing to the overall success of the manufacturing process and customer satisfaction. You will be responsible for contributing to the end-to-end architecture, definition, development and production deployment of production software applications and infrastructure spanning multiple customers and manufacturing regions. You will also be responsible for interfacing with internal engineering, manufacturing and quality teams and our end customers to ensure your software deliverables meet the rigorous standards of Jabil's world-class manufacturing environments. What will you do? - Test System Development: Design and develop test systems and procedures for manufacturing processes. This includes creating test plans, test cases, and test scripts to assess the functionality and performance of hardware components or devices such as motherboard, memory, CPU, storage (SSD, HDD, NVMe) and PCIE devices (NIC, GPU, Mezz cards, RAID cards) Test Software Development: Create, validate, release, and maintain test software and scripts that automate the testing process. This software may include code for controlling test equipment, collecting and analyzing data, and generating test reports Test Sustaining: Support and maintenance for the manufacturing server (L10) and rack (L11) level test software and infrastructure deployed at our production facilities, including the implementation of minor system configuration changes (new IPNs) Documentation: Maintain comprehensive manufacturing server (L10) and rack (L11) documentation of test procedures, specifications, and Infrastructure Collaboration: Work closely with cross-functional teams, including hardware engineers, manufacturing engineers, and quality assurance personnel, to ensure alignment on testing requirements and quality standards Continuous Learning: Stay updated on the latest advancements in testing technologies, methodologies, and industry best practices to keep manufacturing processes competitive and up to date Definition and collaboration on overall test infrastructure and application architectures How will you get here? - Education: BS degree in Electrical/Computer Engineering, Computer Science or related field is required Experience: 5-8 years' experience in a software manufacturing test development/sustaining with enterprise server, storage or networking products is required 10+ years of relevant experience in a software manufacturing test development/ sustaining with enterprise server, storage or networking products and some college coursework in lieu of a 4- yr. degree, will be considered Excellent verbal and written communication skills is required Knowledge, Skills, Abilities: Expertise in the following programming/scripting languages: Python, Java, BASH. C, C++, experience a plus Linux development expertise with a solid understanding of its fundamentals: CentOS/Ubuntu Expertise with hardware and API solutions for controlling, managing and stressing L10 devices (servers, network and storage SSDs, NVMe): IPMI, Redfish, mprime, FIO, Linpack, ptugen, memtester Expertise in the creation and configuration (DHCP, PXE boot, nginx) of Virtual Machines (VMs) using VMWare Expertise with leading edge networking systems, hardware, software and protocols including but not limited to enterprise ethernet datacenter switching/routing L1, L2, and L3 (BGP, DHCP Relay, ECMP). Arista CloudVision is a plus Experience with code versioning tools (Git preferred) Strong knowledge of professional software engineering practices for the complete software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations Ability to travel up to 10% globally as required Preferred Qualifications: MS preferred Experience working in a multi-site and multi-cultural environments is a plus
Cloud Test Development Engineer, Manufacturing
JABIL CIRCUIT, INC Florence, Kentucky
Operating from over 100 facilities in 29 countries, Jabil delivers innovative, integrated, and tailored solutions to customers across a broad range of industries and end-markets, such as automotive, consumer lifestyle and wearable tech, defense and aerospace, connected home and building, industrial and energy, enterprise and infrastructure, healthcare, mobility, packaging and printing. How will you make an impact? Jabil is seeking a Cloud Test Development Engineer, Manufacturing who will directly contribute to the transformative growth within our Enterprise and Infrastructure division by applying unique and innovative approaches to solving problems within a large-scale software production environment. The Software Test Development Engineer plays a vital role in ensuring the quality and reliability of hardware products, contributing to the overall success of the manufacturing process and customer satisfaction. You will be responsible for contributing to the end-to-end architecture, definition, development and production deployment of production software applications and infrastructure spanning multiple customers and manufacturing regions. As the Cloud Test Development Engineer, Manufacturing, you will also be responsible for interfacing internal engineering, manufacturing and quality teams and our end customers to ensure your software deliverables meet the rigorous standards of Jabil's world-class manufacturing environments. What will you do? Test System Development: Design and develop test systems and procedures for manufacturing processes. This includes creating test plans, test cases, and test scripts to assess the functionality and performance of hardware components or devices such as motherboard, memory, CPU, storage (SSD, HDD, NVMe) and PCIE devices (NIC, GPU, Mezz cards, RAID cards) Test Software Development: Create, validate, release, and maintain test software and scripts that automate the testing process. This software may include code for controlling test equipment, collecting, and analyzing data, and generating test reports. Sustaining Test: Support and maintenance for the manufacturing server (L10) and rack (L11) level test software and infrastructure deployed at our production facilities, including the implementation of minor system configuration changes (new IPNs). Documentation: Maintain comprehensive manufacturing server (L10) and rack (L11) documentation of test procedures, specifications, and Infrastructure. Collaboration: Work closely with cross-functional teams, including hardware engineers, manufacturing engineers, and quality assurance personnel, to ensure alignment on testing requirements and quality standards. Continuous Learning: Stay updated on the latest advancements in testing technologies, methodologies, and industry best practices to keep manufacturing processes competitive and up to date. Definition and collaboration on overall test infrastructure and application architectures. Management & Supervisory Responsibilities Reports to Management How will you get here? Expertise in the following programming/scripting languages: Python, BASH, C, C++, experience a plus Linux development expertise with a solid understanding of its fundamentals: CentOS Ubuntu Expertise with hardware and API solutions for controlling, managing, and stressing L10 devices (servers, network, and storage SSDs, NVMe): IPMI, Redfish, mprime, FIO, Linpack, ptugen, memtester Expertise in the creation and configuration (DHCP, PXE boot, nginx) of Virtual Machines (VMs), VMWare preferred. Expertise with leading edge networking systems, hardware, software, and protocols including but not limited to enterprise ethernet datacenter switching/routing L1, L2, and L3 (BGP, DHCP Relay, ECMP). Arista CloudVision is a plus. Experience with code versioning tools (Git preferred). Strong knowledge of professional software engineering practices for the complete software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations. Education: BS degree in Electrical/Computer Engineering, Computer Science, or related field. MS preferred. Experience: 5-8 years' experience in software manufacturing test development/sustaining with enterprise server, storage, or networking products. Excellent verbal and written communication skills. Experience working in multi-site and multi-cultural environments. Domestic and/or international travel, up to 10%, may be required. What Can Jabil Offer You? Along with growth, stability, and the opportunity to be challenged, Jabil offers a competitive benefits package that includes: Medical, Dental, Prescription Drug, and Vision Insurance with HRA and HSA options 401K Match Employee Stock Purchase Plan Paid Time Off Tuition Reimbursement Life, AD&D, and Disability Insurance Commuter Benefits Employee Assistance Program Pet Insurance Adoption Assistance Annual Merit Increases Community Volunteer Opportunities
04/06/2026
Full time
Operating from over 100 facilities in 29 countries, Jabil delivers innovative, integrated, and tailored solutions to customers across a broad range of industries and end-markets, such as automotive, consumer lifestyle and wearable tech, defense and aerospace, connected home and building, industrial and energy, enterprise and infrastructure, healthcare, mobility, packaging and printing. How will you make an impact? Jabil is seeking a Cloud Test Development Engineer, Manufacturing who will directly contribute to the transformative growth within our Enterprise and Infrastructure division by applying unique and innovative approaches to solving problems within a large-scale software production environment. The Software Test Development Engineer plays a vital role in ensuring the quality and reliability of hardware products, contributing to the overall success of the manufacturing process and customer satisfaction. You will be responsible for contributing to the end-to-end architecture, definition, development and production deployment of production software applications and infrastructure spanning multiple customers and manufacturing regions. As the Cloud Test Development Engineer, Manufacturing, you will also be responsible for interfacing internal engineering, manufacturing and quality teams and our end customers to ensure your software deliverables meet the rigorous standards of Jabil's world-class manufacturing environments. What will you do? Test System Development: Design and develop test systems and procedures for manufacturing processes. This includes creating test plans, test cases, and test scripts to assess the functionality and performance of hardware components or devices such as motherboard, memory, CPU, storage (SSD, HDD, NVMe) and PCIE devices (NIC, GPU, Mezz cards, RAID cards) Test Software Development: Create, validate, release, and maintain test software and scripts that automate the testing process. This software may include code for controlling test equipment, collecting, and analyzing data, and generating test reports. Sustaining Test: Support and maintenance for the manufacturing server (L10) and rack (L11) level test software and infrastructure deployed at our production facilities, including the implementation of minor system configuration changes (new IPNs). Documentation: Maintain comprehensive manufacturing server (L10) and rack (L11) documentation of test procedures, specifications, and Infrastructure. Collaboration: Work closely with cross-functional teams, including hardware engineers, manufacturing engineers, and quality assurance personnel, to ensure alignment on testing requirements and quality standards. Continuous Learning: Stay updated on the latest advancements in testing technologies, methodologies, and industry best practices to keep manufacturing processes competitive and up to date. Definition and collaboration on overall test infrastructure and application architectures. Management & Supervisory Responsibilities Reports to Management How will you get here? Expertise in the following programming/scripting languages: Python, BASH, C, C++, experience a plus Linux development expertise with a solid understanding of its fundamentals: CentOS Ubuntu Expertise with hardware and API solutions for controlling, managing, and stressing L10 devices (servers, network, and storage SSDs, NVMe): IPMI, Redfish, mprime, FIO, Linpack, ptugen, memtester Expertise in the creation and configuration (DHCP, PXE boot, nginx) of Virtual Machines (VMs), VMWare preferred. Expertise with leading edge networking systems, hardware, software, and protocols including but not limited to enterprise ethernet datacenter switching/routing L1, L2, and L3 (BGP, DHCP Relay, ECMP). Arista CloudVision is a plus. Experience with code versioning tools (Git preferred). Strong knowledge of professional software engineering practices for the complete software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations. Education: BS degree in Electrical/Computer Engineering, Computer Science, or related field. MS preferred. Experience: 5-8 years' experience in software manufacturing test development/sustaining with enterprise server, storage, or networking products. Excellent verbal and written communication skills. Experience working in multi-site and multi-cultural environments. Domestic and/or international travel, up to 10%, may be required. What Can Jabil Offer You? Along with growth, stability, and the opportunity to be challenged, Jabil offers a competitive benefits package that includes: Medical, Dental, Prescription Drug, and Vision Insurance with HRA and HSA options 401K Match Employee Stock Purchase Plan Paid Time Off Tuition Reimbursement Life, AD&D, and Disability Insurance Commuter Benefits Employee Assistance Program Pet Insurance Adoption Assistance Annual Merit Increases Community Volunteer Opportunities
Cloud Manufacturing Test Development Engineer
JABIL CIRCUIT, INC Florence, Kentucky
Jabil is a product solutions company providing comprehensive design, manufacturing, supply chain and product management services. Operating from over 100 facilities in 29 countries, Jabil delivers innovative, integrated, and tailored solutions to customers across a broad range of industries and end-markets, such as automotive, consumer lifestyle and wearable tech, defense and aerospace, connected home and building, industrial and energy, enterprise and infrastructure, healthcare, mobility, packaging and printing. How will you make an impact? Jabil is seeking a Software Test Development Engineer who will directly contribute to the transformative growth within our Global cloud Test Development (GCTD) team in the Cloud Enterprise and Intelligent Infrastructure (CE&I) division by applying unique and innovative approaches to solving problems within a large-scale software production environment. As the Software Test Development Engineer plays a vital role in ensuring the quality and reliability of hardware products, contributing to the overall success of the manufacturing process and customer satisfaction. You will be responsible for contributing to the end-to-end architecture, definition, development and production deployment of production software applications and infrastructure spanning multiple customers and manufacturing regions. You will also be responsible for interfacing with internal engineering, manufacturing and quality teams and our end customers to ensure your software deliverables meet the rigorous standards of Jabil's world-class manufacturing environments. What will you do? Test System Development: Design and develop test systems and procedures for manufacturing processes. This includes creating test plans, test cases, and test scripts to assess the functionality and performance of hardware components or devices such as: Motherboard, Memory, CPU, Storage (SSD, HDD, NVMe) and PCIE devices (NIC, GPU, Mezz cards, RAID cards) Software Development Test: Create, validate, release, and maintain test software and scripts that automate the testing process. This software may include code for controlling test equipment, collecting and analyzing data, and generating test reports. Sustaining Test: Support and maintenance for the manufacturing server (L10) and rack (L11) level test software and infrastructure deployed at our production facilities, including the implementation of minor system configuration changes (new IPNs). Test Infrastructure Expansions: Support the site's manufacturing server (L10) and rack (L11) current test infrastructure as well as future expansions planning, deployments, and assembly. Debugging and Troubleshooting: Diagnose and resolve issues with test software, or hardware components (servers, switches, racks, L10, L12) that may arise during the manufacturing process. Documentation: Maintain comprehensive manufacturing server (L10) and rack (L11) documentation of test procedures, specifications, and Infrastructure. Collaboration: Work closely with cross-functional teams, including hardware engineers, manufacturing engineers, and quality assurance personnel, to ensure alignment of testing requirements and quality standards. Continuous Learning: Stay updated on the latest advancements in testing technologies, methodologies, and industry best practices to keep manufacturing processes competitive and up to date. Definition and collaboration on overall test infrastructure and application architectures. Management & Supervisory Responsibilities Reports to Management Education: BS degree in Electrical/Computer Engineering, Computer Science or related field. MS preferred Experience: 5 years' experience in software manufacturing test development/sustaining with enterprise servers, storage or networking products. Experience in the following programming/scripting languages: Python, Java, BASH, C, C++, experience a plus Linux development experience with a solid understanding of its fundamentals: CentOS Ubuntu Experience with hardware and API solutions for controlling, managing and stressing L10 devices (servers, network and storage SSDs, NVMe): IPMI, Redfish, mprime, FIO, Linpack, ptugen, memtester Familiarity in the creation and configuration (DHCP, PXE boot, nginx) of Virtual Machines (VMs) using VMWare. Expertise with leading edge networking systems, hardware, software and protocols including but not limited to enterprise ethernet datacenter switching/routing L1, L2, and L3 (BGP, DHCP Relay, ECMP) Arista CloudVision is a plus. Experience with code versioning tools (Git preferred). Knowledge of professional software engineering practices for the complete software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations. Excellent verbal and written communication skills. Experience working in multi-site and multi-cultural environments. What Can Jabil Offer You? Along with growth, stability, and the opportunity to be challenged, Jabil offers a competitive benefits package that includes: Medical, Dental, Prescription Drug, and Vision Insurance with HRA and HSA options 401K Match Employee Stock Purchase Plan Paid Time Off Tuition Reimbursement Life, AD&D, and Disability Insurance Commuter Benefits Employee Assistance Program Pet Insurance Adoption Assistance Annual Merit Increases Community Volunteer Opportunities
04/06/2026
Full time
Jabil is a product solutions company providing comprehensive design, manufacturing, supply chain and product management services. Operating from over 100 facilities in 29 countries, Jabil delivers innovative, integrated, and tailored solutions to customers across a broad range of industries and end-markets, such as automotive, consumer lifestyle and wearable tech, defense and aerospace, connected home and building, industrial and energy, enterprise and infrastructure, healthcare, mobility, packaging and printing. How will you make an impact? Jabil is seeking a Software Test Development Engineer who will directly contribute to the transformative growth within our Global cloud Test Development (GCTD) team in the Cloud Enterprise and Intelligent Infrastructure (CE&I) division by applying unique and innovative approaches to solving problems within a large-scale software production environment. As the Software Test Development Engineer plays a vital role in ensuring the quality and reliability of hardware products, contributing to the overall success of the manufacturing process and customer satisfaction. You will be responsible for contributing to the end-to-end architecture, definition, development and production deployment of production software applications and infrastructure spanning multiple customers and manufacturing regions. You will also be responsible for interfacing with internal engineering, manufacturing and quality teams and our end customers to ensure your software deliverables meet the rigorous standards of Jabil's world-class manufacturing environments. What will you do? Test System Development: Design and develop test systems and procedures for manufacturing processes. This includes creating test plans, test cases, and test scripts to assess the functionality and performance of hardware components or devices such as: Motherboard, Memory, CPU, Storage (SSD, HDD, NVMe) and PCIE devices (NIC, GPU, Mezz cards, RAID cards) Software Development Test: Create, validate, release, and maintain test software and scripts that automate the testing process. This software may include code for controlling test equipment, collecting and analyzing data, and generating test reports. Sustaining Test: Support and maintenance for the manufacturing server (L10) and rack (L11) level test software and infrastructure deployed at our production facilities, including the implementation of minor system configuration changes (new IPNs). Test Infrastructure Expansions: Support the site's manufacturing server (L10) and rack (L11) current test infrastructure as well as future expansions planning, deployments, and assembly. Debugging and Troubleshooting: Diagnose and resolve issues with test software, or hardware components (servers, switches, racks, L10, L12) that may arise during the manufacturing process. Documentation: Maintain comprehensive manufacturing server (L10) and rack (L11) documentation of test procedures, specifications, and Infrastructure. Collaboration: Work closely with cross-functional teams, including hardware engineers, manufacturing engineers, and quality assurance personnel, to ensure alignment of testing requirements and quality standards. Continuous Learning: Stay updated on the latest advancements in testing technologies, methodologies, and industry best practices to keep manufacturing processes competitive and up to date. Definition and collaboration on overall test infrastructure and application architectures. Management & Supervisory Responsibilities Reports to Management Education: BS degree in Electrical/Computer Engineering, Computer Science or related field. MS preferred Experience: 5 years' experience in software manufacturing test development/sustaining with enterprise servers, storage or networking products. Experience in the following programming/scripting languages: Python, Java, BASH, C, C++, experience a plus Linux development experience with a solid understanding of its fundamentals: CentOS Ubuntu Experience with hardware and API solutions for controlling, managing and stressing L10 devices (servers, network and storage SSDs, NVMe): IPMI, Redfish, mprime, FIO, Linpack, ptugen, memtester Familiarity in the creation and configuration (DHCP, PXE boot, nginx) of Virtual Machines (VMs) using VMWare. Expertise with leading edge networking systems, hardware, software and protocols including but not limited to enterprise ethernet datacenter switching/routing L1, L2, and L3 (BGP, DHCP Relay, ECMP) Arista CloudVision is a plus. Experience with code versioning tools (Git preferred). Knowledge of professional software engineering practices for the complete software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations. Excellent verbal and written communication skills. Experience working in multi-site and multi-cultural environments. What Can Jabil Offer You? Along with growth, stability, and the opportunity to be challenged, Jabil offers a competitive benefits package that includes: Medical, Dental, Prescription Drug, and Vision Insurance with HRA and HSA options 401K Match Employee Stock Purchase Plan Paid Time Off Tuition Reimbursement Life, AD&D, and Disability Insurance Commuter Benefits Employee Assistance Program Pet Insurance Adoption Assistance Annual Merit Increases Community Volunteer Opportunities
Senior Manufacturing Test Development Engineer
JABIL CIRCUIT, INC Washington, Washington DC
Location/Division Specific Information - Austin, TX/ USA - Remote This position supports hybrid work schedule depending on organization needs. How will you make an impact? - Jabil is seeking a Sr. Software Test Development Engineer who will directly contribute to the transformative growth within our Enterprise and Infrastructure division by applying unique and innovative approaches to solving problems within a large-scale software production environment. The Software Test Development Engineer play a vital role in ensuring the quality and reliability of hardware products, contributing to the overall success of the manufacturing process and customer satisfaction. You will be responsible for contributing to the end-to-end architecture, definition, development and production deployment of production software applications and infrastructure spanning multiple customers and manufacturing regions. You will also be responsible for interfacing with internal engineering, manufacturing and quality teams and our end customers to ensure your software deliverables meet the rigorous standards of Jabil's world-class manufacturing environments. What will you do? - Test System Development: Design and develop test systems and procedures for manufacturing processes. This includes creating test plans, test cases, and test scripts to assess the functionality and performance of hardware components or devices such as motherboard, memory, CPU, storage (SSD, HDD, NVMe) and PCIE devices (NIC, GPU, Mezz cards, RAID cards) Test Software Development: Create, validate, release, and maintain test software and scripts that automate the testing process. This software may include code for controlling test equipment, collecting and analyzing data, and generating test reports Test Sustaining: Support and maintenance for the manufacturing server (L10) and rack (L11) level test software and infrastructure deployed at our production facilities, including the implementation of minor system configuration changes (new IPNs) Documentation: Maintain comprehensive manufacturing server (L10) and rack (L11) documentation of test procedures, specifications, and Infrastructure Collaboration: Work closely with cross-functional teams, including hardware engineers, manufacturing engineers, and quality assurance personnel, to ensure alignment on testing requirements and quality standards Continuous Learning: Stay updated on the latest advancements in testing technologies, methodologies, and industry best practices to keep manufacturing processes competitive and up to date Definition and collaboration on overall test infrastructure and application architectures How will you get here? - Education: BS degree in Electrical/Computer Engineering, Computer Science or related field is required Experience: 5-8 years' experience in a software manufacturing test development/sustaining with enterprise server, storage or networking products is required 10+ years of relevant experience in a software manufacturing test development/ sustaining with enterprise server, storage or networking products and some college coursework in lieu of a 4- yr. degree, will be considered Excellent verbal and written communication skills is required Knowledge, Skills, Abilities: Expertise in the following programming/scripting languages: Python, Java, BASH. C, C++, experience a plus Linux development expertise with a solid understanding of its fundamentals: CentOS/Ubuntu Expertise with hardware and API solutions for controlling, managing and stressing L10 devices (servers, network and storage SSDs, NVMe): IPMI, Redfish, mprime, FIO, Linpack, ptugen, memtester Expertise in the creation and configuration (DHCP, PXE boot, nginx) of Virtual Machines (VMs) using VMWare Expertise with leading edge networking systems, hardware, software and protocols including but not limited to enterprise ethernet datacenter switching/routing L1, L2, and L3 (BGP, DHCP Relay, ECMP). Arista CloudVision is a plus Experience with code versioning tools (Git preferred) Strong knowledge of professional software engineering practices for the complete software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations Ability to travel up to 10% globally as required Preferred Qualifications: MS preferred Experience working in a multi-site and multi-cultural environments is a plus
04/06/2026
Full time
Location/Division Specific Information - Austin, TX/ USA - Remote This position supports hybrid work schedule depending on organization needs. How will you make an impact? - Jabil is seeking a Sr. Software Test Development Engineer who will directly contribute to the transformative growth within our Enterprise and Infrastructure division by applying unique and innovative approaches to solving problems within a large-scale software production environment. The Software Test Development Engineer play a vital role in ensuring the quality and reliability of hardware products, contributing to the overall success of the manufacturing process and customer satisfaction. You will be responsible for contributing to the end-to-end architecture, definition, development and production deployment of production software applications and infrastructure spanning multiple customers and manufacturing regions. You will also be responsible for interfacing with internal engineering, manufacturing and quality teams and our end customers to ensure your software deliverables meet the rigorous standards of Jabil's world-class manufacturing environments. What will you do? - Test System Development: Design and develop test systems and procedures for manufacturing processes. This includes creating test plans, test cases, and test scripts to assess the functionality and performance of hardware components or devices such as motherboard, memory, CPU, storage (SSD, HDD, NVMe) and PCIE devices (NIC, GPU, Mezz cards, RAID cards) Test Software Development: Create, validate, release, and maintain test software and scripts that automate the testing process. This software may include code for controlling test equipment, collecting and analyzing data, and generating test reports Test Sustaining: Support and maintenance for the manufacturing server (L10) and rack (L11) level test software and infrastructure deployed at our production facilities, including the implementation of minor system configuration changes (new IPNs) Documentation: Maintain comprehensive manufacturing server (L10) and rack (L11) documentation of test procedures, specifications, and Infrastructure Collaboration: Work closely with cross-functional teams, including hardware engineers, manufacturing engineers, and quality assurance personnel, to ensure alignment on testing requirements and quality standards Continuous Learning: Stay updated on the latest advancements in testing technologies, methodologies, and industry best practices to keep manufacturing processes competitive and up to date Definition and collaboration on overall test infrastructure and application architectures How will you get here? - Education: BS degree in Electrical/Computer Engineering, Computer Science or related field is required Experience: 5-8 years' experience in a software manufacturing test development/sustaining with enterprise server, storage or networking products is required 10+ years of relevant experience in a software manufacturing test development/ sustaining with enterprise server, storage or networking products and some college coursework in lieu of a 4- yr. degree, will be considered Excellent verbal and written communication skills is required Knowledge, Skills, Abilities: Expertise in the following programming/scripting languages: Python, Java, BASH. C, C++, experience a plus Linux development expertise with a solid understanding of its fundamentals: CentOS/Ubuntu Expertise with hardware and API solutions for controlling, managing and stressing L10 devices (servers, network and storage SSDs, NVMe): IPMI, Redfish, mprime, FIO, Linpack, ptugen, memtester Expertise in the creation and configuration (DHCP, PXE boot, nginx) of Virtual Machines (VMs) using VMWare Expertise with leading edge networking systems, hardware, software and protocols including but not limited to enterprise ethernet datacenter switching/routing L1, L2, and L3 (BGP, DHCP Relay, ECMP). Arista CloudVision is a plus Experience with code versioning tools (Git preferred) Strong knowledge of professional software engineering practices for the complete software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations Ability to travel up to 10% globally as required Preferred Qualifications: MS preferred Experience working in a multi-site and multi-cultural environments is a plus
Senior Lead AI Engineer (Gen AI Platform Services)
Capital One New York, New York
Senior Lead AI Engineer (Gen AI Platform Services) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Senior Lead AI Engineer (Gen AI Platform Services) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead AI Engineer (MLX)
Capital One Mc Lean, Virginia
Lead AI Engineer (MLX) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Lead AI Engineer (MLX) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Lead AI Engineer ( MLX, Gen AI Platform Services, Agentic AI)
Capital One New York, New York
Sr. Lead AI Engineer ( MLX, Gen AI Platform Services, Agentic AI) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Sr. Lead AI Engineer ( MLX, Gen AI Platform Services, Agentic AI) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead AI Engineer (GenAI Platform Services)
Capital One Mc Lean, Virginia
Lead AI Engineer (GenAI Platform Services) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Lead AI Engineer (GenAI Platform Services) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services)
Capital One New York, New York
Senior Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Senior Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Lead, Machine Learning Engineer (GenAI, Python, AWS)
Capital One Richmond, Virginia
Senior Lead, Machine Learning Engineer (GenAI, Python, AWS) As a Capital One Senior Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Operations, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: 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. 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). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. 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. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. 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. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer Richmond, VA: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Senior Lead, Machine Learning Engineer (GenAI, Python, AWS) As a Capital One Senior Lead Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: The MLE role overlaps with many disciplines, such as Operations, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: 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. 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). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. 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. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. 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. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply) At least 4 years of experience programming with Python, Scala, or Java At least 3 years of experience building, scaling, and optimizing ML systems At least 2 years of experience leading teams developing ML solutions Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models 3+ years of people management experience ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents 3+ years of experience building production-ready data pipelines that feed ML models Ability to communicate complex technical concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead Machine Learning Engineer Richmond, VA: $209,000 - $238,500 for Sr. Lead Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior AI Engineer (Gen AI Platform Services, Agentic Systems)
Capital One Mc Lean, Virginia
Senior AI Engineer (Gen AI Platform Services, Agentic Systems) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 3 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 1 year of experience developing AI and ML algorithms or technologies At least 3 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 4 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $161,800 - $184,600 for Senior AI Engineer McLean, VA: $161,800 - $184,600 for Senior AI Engineer New York, NY: $176,500 - $201,400 for Senior AI Engineer San Francisco, CA: $176,500 - $201,400 for Senior AI Engineer San Jose, CA: $176,500 - $201,400 for Senior AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Senior AI Engineer (Gen AI Platform Services, Agentic Systems) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 3 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 1 year of experience developing AI and ML algorithms or technologies At least 3 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 4 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $161,800 - $184,600 for Senior AI Engineer McLean, VA: $161,800 - $184,600 for Senior AI Engineer New York, NY: $176,500 - $201,400 for Senior AI Engineer San Francisco, CA: $176,500 - $201,400 for Senior AI Engineer San Jose, CA: $176,500 - $201,400 for Senior AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Machine Learning Engineer
Capital One Richmond, Virginia
Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: 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: 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. 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). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. 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. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. 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. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). 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. Chicago, IL: $147,100 - $167,900 for Senior Machine Learning Engineer McLean, VA: $161,800 - $184,600 for Senior Machine Learning Engineer Plano, TX: $147,100 - $167,900 for Senior Machine Learning Engineer Richmond, VA: $147,100 - $167,900 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering. What you'll do in the role: 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: 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. 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). Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment. 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. Retrain, maintain, and monitor models in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. 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. Use programming languages like Python, Scala, or Java. Basic Qualifications: Bachelor's Degree At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply) At least 3 years of experience designing and building data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1+ years of experience building, scaling, and optimizing ML systems 1+ years of experience with data gathering and preparation for ML models 2+ years of experience developing performant, resilient, and maintainable code Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field 3+ years of experience with distributed file systems or multi-node database paradigms Contributed to open source ML software Authored/co-authored a paper on a ML technique, model, or proof of concept 3+ years of experience building production-ready data pipelines that feed ML models Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer). 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. Chicago, IL: $147,100 - $167,900 for Senior Machine Learning Engineer McLean, VA: $161,800 - $184,600 for Senior Machine Learning Engineer Plano, TX: $147,100 - $167,900 for Senior Machine Learning Engineer Richmond, VA: $147,100 - $167,900 for Senior Machine Learning Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)
Capital One Mc Lean, Virginia
Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration)
Capital One New York, New York
Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Lead AI Engineer (Gen AI Platform, Agentic AI & LLM Infrastructure & Orchestration) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Lead AI Engineer (AI Foundations, LLM Customization and Finetuning)
Capital One Mc Lean, Virginia
Lead AI Engineer (AI Foundations, LLM Customization and Finetuning) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Lead AI Engineer (AI Foundations, LLM Customization and Finetuning) Overview At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies At least 4 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting AI services Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer McLean, VA: $197,300 - $225,100 for Lead AI Engineer New York, NY: $215,200 - $245,600 for Lead AI Engineer San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer San Jose, CA: $215,200 - $245,600 for Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Sr. Lead AI Engineer ( MLX, Gen AI Platform Services, Agentic AI)
Capital One Mc Lean, Virginia
Sr. Lead AI Engineer ( MLX, Gen AI Platform Services, Agentic AI) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Sr. Lead AI Engineer ( MLX, Gen AI Platform Services, Agentic AI) Overview: At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer Cambridge, MA: $229,900 - $262,400 for Sr. Lead AI Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. Lead AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Distinguished AI Engineer
Capital One New York, New York
Senior Distinguished AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 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 At least 10 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex enterprise AI systems Demonstrated ability to lead and mentor an engineering organization and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
04/06/2026
Full time
Senior Distinguished AI Engineer At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven. You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 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 At least 10 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience architecting, designing, developing, integrating, delivering, and supporting complex enterprise AI systems Demonstrated ability to lead and mentor an engineering organization and influence cross-functional stakeholders up to the SVP level Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $314,800 - $359,300 for Sr. Distinguished AI Engineer McLean, VA: $314,800 - $359,300 for Sr. Distinguished AI Engineer New York, NY: $343,400 - $392,000 for Sr. Distinguished AI Engineer Richmond, VA: $286,200 - $326,700 for Sr. Distinguished AI Engineer San Francisco, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer San Jose, CA: $343,400 - $392,000 for Sr. Distinguished AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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