Senior Lead Machine Learning Engineer (Intelligent Foundations and Experiences)

Capital One invites a Senior Lead Machine Learning Engineer to join onsite in McLean, VA. This role focuses on productionizing ML at scale, shaping architecture, development, and deployment of AI-powered products. You will lead dedicated pods of software, data, and ML engineers to ensure high availability and strong performance, while driving innovative solutions in Credit and Financial Risk Management. The annual compensation ranges from USD 229,900 to 262,400.

Benefits

• Health benefits
• Financial benefits
• Incentives (performance-based incentive compensation, including cash bonuses and/or long-term incentives)
• Other benefits

Responsibilities

• Direct cross-disciplinary pods of software, data, and ML engineers to build AI and ML capabilities for Credit and Financial Risk Management, acting as a technical mentor on core technologies
• Design, develop, and deliver AI powered products and components that address real business needs, applying model experimentation, LLM inference, similarity search, and agentic AI within a collaborative Product and Data Science environment
• Partner with engineers, data scientists, and designers to scale AI powered solutions that improve associate performance and deliver exceptional customer value
• Inform ML infrastructure choices by applying knowledge of modeling techniques, including model type, data and feature selection, training, hyperparameters, dimensionality, bias/variance, and validation
• Tackle complex problems by writing and testing application code, building and validating ML models, and automating tests and deployment
• Retrain, maintain, and monitor models in production to ensure ongoing effectiveness
• Utilize or build cloud-based architectures and platforms to deploy optimized ML models at scale
• Construct efficient data pipelines to feed ML models
• Apply continuous integration and continuous deployment practices, including test automation and monitoring
• Govern code quality and model governance, ensuring Responsible and Explainable AI practices
• Leverage a broad stack of Open Source and SaaS AI technologies and work with languages such as Python, Scala, and Java
• Key technologies you may work with include Python, Scala, Java, AWS Bedrock, Google Cloud, and Azure

Requirements

• Bachelor’s Degree
• At least 8 years designing and building data-intensive solutions using distributed computing (internship experience does not apply)
• At least 4 years programming with Python, Scala, or Java
• At least 3 years building, scaling, and optimizing ML systems
• At least 2 years leading teams developing ML solutions