Senior Lead Machine Learning Engineer (Intelligent Foundations and Experiences)

Capital One seeks a Senior Lead Machine Learning Engineer to scale ML applications and shape their architecture, development, and deployment. You will lead dedicated pods of software, data, and ML engineers to deliver AI powered products with high availability and strong performance. This onsite role is based in McLean, Virginia, with a salary range of USD 229,900 to 262,400 per year and requires a Bachelor's Degree.

Responsibilities

• Lead dedicated pods of software, data, and machine learning engineers to build AI and ML capabilities for Credit and Financial Risk Management products, mentoring the team on these core technologies.
• Design and deliver AI powered products and components that solve real world business problems, applying model experimentation, LLM inference, similarity search, and agentic AI within a collaborative Product and Data Science environment.
• Collaborate with a cross functional team of engineers, data scientists, and designers to develop and scale AI powered products that improve associate performance and deliver world class customer value.
• Inform ML infrastructure decisions by applying knowledge of modeling techniques and issues, including model choice, data and feature selection, training, hyperparameter tuning, dimensionality, bias and variance, and validation.
• Address complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud based architectures, technologies, and platforms to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Apply 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 responsible and explainable AI practices.
• Leverage a broad stack of Open Source and SaaS AI technologies and use programming languages like Python, Scala, or Java.

Requirements

• Bachelor’s Degree
• Minimum 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

Technologies

• Python
• Scala
• Java
• AWS Bedrock
• Google Cloud
• Azure

Benefits

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