Lead Machine Learning Engineer

Capital One seeks a Lead Machine Learning Engineer for an onsite role in McLean, VA. This position focuses on productionizing ML applications and scalable systems within an Agile team, emphasizing collaboration, governance, and measurable impact. The role offers a competitive annual compensation between USD 197,300 and 225,100, along with comprehensive health and financial benefits and performance-based incentives. A Bachelor’s degree is required.

Benefits

• Health benefits
• Financial benefits
• Other benefits
• Performance-based incentive compensation (cash bonuses and/or long-term incentives)

Responsibilities

• Design, build, and deliver ML models and components that address real-world business needs, collaborating with Product and Data Science teams
• Inform ML infrastructure choices using modeling expertise, including model selection, data and feature choices, training, 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
• Work within a cross-functional Agile team to create and improve software powering advanced big data and ML applications
• Retrain, maintain, and monitor models in production
• Leverage or build cloud-based architectures and platforms to deliver optimized ML models at scale
• Construct optimized data pipelines to feed ML models
• Apply continuous integration and continuous deployment practices, including test automation and monitoring, to ensure successful deployment
• Keep code well-managed to reduce vulnerabilities and ensure model governance, following Responsible and Explainable AI best practices
• Use programming languages such as Python, Scala, or Java

Requirements

• 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, Scala, or Java
• At least 2 years of experience building, scaling, and optimizing ML systems

Technologies

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

Preferred Qualifications

• Master's or Doctoral degree in computer science, electrical engineering, mathematics, or a related field
• 3+ years building production-ready data pipelines feeding ML models
• 3+ years of hands-on experience with industry-standard ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 2+ years of delivering performant, resilient, and maintainable code
• 2+ years of data gathering and preparation for ML models
• 2+ years of people leadership experience
• 1+ years leading teams developing ML solutions using industry best practices, patterns, and automation
• Experience deploying ML solutions in public cloud environments like AWS, Azure, or Google Cloud
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• Contributions to ML industry impact through conferences, papers, blog posts, open source, or patents
• Experience using interactive AI tooling to increase productivity beyond basic code completion