Lead Machine Learning Engineer role at Capital One, onsite in McLean, VA, focused on productionizing ML applications and systems at scale.

Design, develop, and deliver ML models and components to address real world business needs, collaborating with Product and Data Science teams
Guide ML infrastructure choices using modeling considerations such as model type, data, feature engineering, training, hyperparameters, dimensionality, bias and variance, and validation
Tackle complex problems by writing and testing application code, building and validating ML models, and automating tests and deployment
Work within a cross functional Agile team to create software that enables advanced big data and ML applications
Retrain, monitor, and maintain models in production environments
Leverage or build cloud based architectures to deploy optimized ML models at scale
Construct efficient data pipelines to feed ML models
Apply continuous integration and deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and code
Ensure code quality, governance, and risk controls, and promote Responsible and Explainable AI practices
Proficient in Python, Scala, or Java

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

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

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 hands on experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
2+ years writing performant, resilient, and maintainable code
2+ years gathering and preparing data for ML models
2+ years people leadership experience
1+ years leading teams developing ML solutions using best practices, patterns, and automation
Experience developing and deploying ML solutions in AWS, Azure, or Google Cloud Platform
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
Demonstrated ML industry impact through conference talks, papers, blog posts, open source contributions, or patents
Experience using interactive AI tooling to accelerate productivity beyond basic code completion

Lead Machine Learning Engineer

Job Description