NLP PEOPLE
Lead Machine Learning Engineer – ML/AI
At Capital One, we are changing banking for good by creating responsible and reliable AI‑powered systems. 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 bring humanity and simplicity to banking. We are committed to building world‑class applied science and engineering teams to deliver industry‑leading capabilities with breakthrough product experiences and scalable, high‑performance AI infrastructure.
In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data‑driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities.
Responsibilities
Partner with a cross‑functional team of engineers, data scientists, product managers, and designers to deliver AI‑powered products that change how our associates work and provide value to our customers.
Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI.
Fine‑tune, develop and evaluate machine learning and foundation models.
Collaborate on a cross‑functional Agile team to create and enhance software that utilizes state‑of‑the‑art AI and ML capabilities.
Contribute thought leadership and technical vision to the long‑term roadmap of pioneering AI systems at Capital One.
Leverage a broad stack of open source and SaaS AI technologies.
Inform ML infrastructure decisions using your understanding of ML modeling techniques and issues.
Retrain, maintain, and monitor models in production.
Construct optimized data pipelines to feed ML models.
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.
Ideal Candidate
You love to build systems, take pride in the quality of your work, and share our passion to do the right thing. You want to work on problems that will help change banking for good.
You are a passionate communicator, comfortable explaining complex technical concepts to non‑technical partners across the business, sometimes in front of large audiences.
You stay abreast of the latest research, and can 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, digging deep to uncover the root of problems, and can articulate your findings concisely.
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.
You are strategic and business‑oriented: you think beyond the technology, deeply understand business needs and how AI can solve them.
You are highly collaborative and transparent: you work seamlessly across engineering, product, and data‑science teams, communicate progress and blockers clearly and proactively.
You are technically mature and humble: you bring clarity to complex, undefined problems and can articulate findings concisely.
You are flexible & fungible: you enjoy rolling up your sleeves and contributing wherever the team needs you most.
You are a lifelong learner: you stay current with AI research and apply novel techniques to production systems judiciously, always focusing on business impact.
Basic Qualifications
Bachelor’s degree.
At least 6 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, Go, Scala, or Java.
At least 3 years of experience deploying scalable software solutions on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
Preferred Qualifications
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.
6 years of experience designing, developing, delivering, and supporting AI services at scale.
3 years of experience developing AI and ML algorithms or technologies using Python.
2 years of experience with Retrieval Augmented Generation (RAG).
Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure.
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
Salary & Benefits The minimum and maximum full‑time annual salaries for this role vary by location: Cambridge, MA – $193,400 – $220,700; McLean, VA – $193,400 – $220,700; New York, NY – $211,000 – $240,800; Richmond, VA – $175,800 – $200,700. This role is also eligible for performance‑based incentive compensation, including cash bonuses and/or long‑term incentives.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being.
EEO Statement 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 and will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws.
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In Risk Tech, we provide the foundation for Capital One to thrive in an uncertain world. Our engaged, empowered, and intelligent people produce outstanding products, working toward the common goal of transforming risk management with technology. We build data‑driven tools that use machine learning to prevent risks & automatically detect issues before they impact our customers, our business, or our communities.
Responsibilities
Partner with a cross‑functional team of engineers, data scientists, product managers, and designers to deliver AI‑powered products that change how our associates work and provide value to our customers.
Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI.
Fine‑tune, develop and evaluate machine learning and foundation models.
Collaborate on a cross‑functional Agile team to create and enhance software that utilizes state‑of‑the‑art AI and ML capabilities.
Contribute thought leadership and technical vision to the long‑term roadmap of pioneering AI systems at Capital One.
Leverage a broad stack of open source and SaaS AI technologies.
Inform ML infrastructure decisions using your understanding of ML modeling techniques and issues.
Retrain, maintain, and monitor models in production.
Construct optimized data pipelines to feed ML models.
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.
Ideal Candidate
You love to build systems, take pride in the quality of your work, and share our passion to do the right thing. You want to work on problems that will help change banking for good.
You are a passionate communicator, comfortable explaining complex technical concepts to non‑technical partners across the business, sometimes in front of large audiences.
You stay abreast of the latest research, and can 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, digging deep to uncover the root of problems, and can articulate your findings concisely.
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.
You are strategic and business‑oriented: you think beyond the technology, deeply understand business needs and how AI can solve them.
You are highly collaborative and transparent: you work seamlessly across engineering, product, and data‑science teams, communicate progress and blockers clearly and proactively.
You are technically mature and humble: you bring clarity to complex, undefined problems and can articulate findings concisely.
You are flexible & fungible: you enjoy rolling up your sleeves and contributing wherever the team needs you most.
You are a lifelong learner: you stay current with AI research and apply novel techniques to production systems judiciously, always focusing on business impact.
Basic Qualifications
Bachelor’s degree.
At least 6 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, Go, Scala, or Java.
At least 3 years of experience deploying scalable software solutions on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
Preferred Qualifications
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.
6 years of experience designing, developing, delivering, and supporting AI services at scale.
3 years of experience developing AI and ML algorithms or technologies using Python.
2 years of experience with Retrieval Augmented Generation (RAG).
Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, Azure.
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance.
Salary & Benefits The minimum and maximum full‑time annual salaries for this role vary by location: Cambridge, MA – $193,400 – $220,700; McLean, VA – $193,400 – $220,700; New York, NY – $211,000 – $240,800; Richmond, VA – $175,800 – $200,700. This role is also eligible for performance‑based incentive compensation, including cash bonuses and/or long‑term incentives.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well‑being.
EEO Statement 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 and will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws.
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