Sr. Lead Machine Learning Engineer

Build and productionize machine learning at scale with Capital One on an Agile team. This on-site role in McLean, VA combines model engineering, ML application development, and production monitoring, with a focus on delivering real-world business impact while supporting Responsible and Explainable AI and strong risk governance.

Compensation: USD 229,900 - 262,400 per year (McLean, VA). Capital One also offers performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI), plus a comprehensive, competitive, and inclusive benefits package covering health, financial, and other support for your total well-being.

What you’ll do

• Design, build, and deliver machine learning models and components that address business problems in collaboration with Product and Data Science.
• Use ML expertise to guide infrastructure and modeling decisions, including model selection, data and feature selection, training, hyperparameter tuning, dimensionality considerations, and validation with attention to bias/variance.
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment.
• Work within a cross-functional Agile environment to create and enhance software supporting big data and ML applications.
• Retrain, maintain, and monitor models in production.
• 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 CI/CD best practices including test automation and monitoring to support successful deployment of ML models and ML application code.
• Ensure code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and ML follows Responsible and Explainable AI best practices.
• Use programming languages such as Python, Scala, or Java to deliver production solutions.

Requirements

• Bachelor’s Degree
• At least 8 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 3 years of experience building, scaling, and optimizing ML systems
• At least 2 years of experience leading teams developing ML solutions

Preferred qualifications

• 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 of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, Kubeflow, or TensorFlow
• 3+ years of experience developing performant, resilient, and maintainable code
• 3+ years of experience with data gathering and preparation for ML models
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
• 3+ years of experience building production-ready data pipelines that feed ML models
• Ability to communicate complex technical concepts clearly to a variety of audiences

Technologies: Python, Scala, Java, AWS, Azure, Google Cloud Platform, scikit-learn, PyTorch, Dask, Spark, Kubeflow, TensorFlow.

Other role details

• Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
• This role is expected to accept applications for a minimum of 5 business days.
• No agencies please.
• Equal Opportunity Employer (EOE, including disability/vet), committed to non-discrimination in compliance with applicable federal, state, and local laws.
• Capital One promotes a drug-free workplace.
• Capital One does not provide, endorse, nor guarantee third-party products, services, educational tools, or other information available through this site.
• Candidates hired to work in other locations will be subject to the pay range associated with that location.