Sr. Lead Machine Learning Engineer

Capital One is seeking a Sr. Lead Machine Learning Engineer to join an Agile team focused on productionizing machine learning applications at scale. This onsite role in New York, NY blends engineering depth with responsible model delivery, from architectural design and deployment automation to ongoing monitoring and governance. You will help build and enhance software that supports state-of-the-art big data and ML workloads, while collaborating closely with Product and Data Science teams.

What you’ll do

• Design, build, and deliver machine learning models and components that address real business needs in collaboration with Product and Data Science teams
• Guide ML infrastructure decisions using expertise in modeling and training topics such as model choice, data and feature selection, hyperparameter tuning, dimensionality, bias/variance, and validation
• Tackle complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
• Contribute within a cross-functional Agile team to create and enhance software for large-scale big data and ML applications
• Retrain, maintain, and monitor models in production, including model governance from a risk perspective
• Leverage or build cloud-based architectures and platforms to deliver optimized ML models at scale
• Construct optimized data pipelines that feed ML models
• Apply CI/CD best practices, including test automation and monitoring, to support successful deployment of ML models and application code
• Use programming languages such as Python, Scala, or Java to build well-managed code and follow best practices in Responsible and Explainable AI

What you’ll bring

• Bachelor’s Degree
• 8+ years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply)
• 4+ years programming with Python, Scala, or Java
• 3+ years building, scaling, and optimizing ML systems
• 2+ years leading teams developing ML solutions
• 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 on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or XGBoost
• 3+ years developing performant, resilient, and maintainable code
• 3+ years of 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 building production-ready data pipelines that feed ML models
• Ability to communicate complex technical concepts clearly to a variety of audiences
• Experience leveraging interactive AI tooling to accelerate productivity beyond basic code completion

Tools you’ll work with

Python, Scala, Java, AWS, Azure, Google Cloud Platform, scikit-learn, PyTorch, Dask, Spark, XGboost

Compensation and benefits

Salary: USD 250,800 - 286,200 per year.

• Comprehensive, competitive, and inclusive health, financial, and other benefits that support your total well-being
• Performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)