Lead Machine Learning Engineer

Capital One is hiring a Lead Machine Learning Engineer (Manager IC) for an onsite Agile team in McLean, VA to design and productionize foundation models using self-supervised learning for transformer architectures.

Responsibilities

• Support detailed technical design, development, and implementation across model architecture, large-scale training, and representation learning for transformer-based foundation models
• Develop and review model and application code; drive ML architectural decisions to ensure high availability and performance of production applications
• Design, build, and/or deliver ML models and components that address real business needs while collaborating with Product and Data Science teams
• Apply ML modeling knowledge to guide infrastructure decisions, including choices around model, data, feature selection, training, hyperparameter tuning, dimensionality, bias/variance, and validation
• Address complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
• Collaborate with a cross-functional Agile team to create and improve software supporting state-of-the-art big data and ML applications
• Retrain, maintain, and monitor models once deployed in production
• Leverage and/or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale
• Construct optimized data pipelines to feed ML models
• Use continuous integration and continuous deployment practices, including test automation and monitoring, to support successful releases
• Ensure code is well-managed to reduce vulnerabilities; support model governance from a risk perspective; follow Responsible and Explainable AI best practices
• Use programming languages such as Python, Scala, or Java

Requirements

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

Technologies

• Python, Scala, Java
• scikit-learn, PyTorch, TensorFlow
• Dask, Spark
• 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 that feed ML models
• 3+ years on-the-job experience with an industry-recognized ML framework: scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 2+ years developing performant, resilient, and maintainable code
• 2+ years experience with data gathering and preparation for ML models
• 2+ years people leader experience
• 1+ years experience leading teams developing ML solutions using industry best practices, patterns, and automation
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
• ML industry impact via conference presentations, papers, blog posts, open source contributions, or patents
• Experience leveraging interactive AI tooling to accelerate productivity beyond basic code completion

Location and Compensation

• Location: McLean, VA (onsite)
• Salary Range: USD 197,300 - 225,100 per year
• Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

Additional Information

• No agencies please
• Capital One will not sponsor a new applicant for employment authorization or provide immigration related support for this position (including H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1, O-1, and other work authorization requiring employer support)
• Expected application review window: minimum of 5 business days
• Capital One is an equal opportunity employer (EOE), committed to non-discrimination in compliance with applicable federal, state, and local laws
• Capital One promotes a drug-free workplace
• Accommodation request: 1-800-304-9102 or [email protected]
• Recruiting process support: [email protected]