Sr. Lead Machine Learning Engineer

Capital One is hiring a Sr. Lead Machine Learning Engineer for an Agile team focused on productionizing machine learning applications at scale. This onsite role in New York, NY blends ML architecture, engineering, and responsible governance so teams can deliver real-world impact with dependable systems.

Compensation: USD 250,800 to 286,200 per year.

What you’ll do

• Design, build, and/or deliver machine learning models and components that address business problems in collaboration with Product and Data Science teams.
• Shape ML infrastructure decisions using hands-on expertise across model and data choices, including feature selection, training, hyperparameter tuning, dimensionality, and concepts like bias/variance and validation.
• Develop and validate ML solutions through application code, testing, and test automation, while enabling smooth deployment of models and supporting software.
• Work within a cross-functional Agile team to create and enhance software for state-of-the-art big data and ML applications.
• Retrain, maintain, and monitor models in production, supporting ongoing performance and reliability.
• 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.
• Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to support successful releases.
• Ensure code quality and governance, reduce vulnerabilities, and support Responsible and Explainable AI best practices from a risk perspective.
• Use programming languages including Python, Scala, or Java.

What you 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 experience leading teams developing ML solutions.
• Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or similar.
• 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 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.

Skills and tools

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

Benefits

• Comprehensive, competitive, and inclusive set of 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).