Sr. Lead Machine Learning Engineer

Capital One seeks a Senior Lead Machine Learning Engineer to design, develop, and productionize scalable ML solutions within an Agile team. The role emphasizes ML design, model and application code review, and maintaining high availability and performance. This on-site position is based in McLean, VA with a salary range of USD 229,900 to 262,400 per year.

Role Details

• Location: McLean, VA (onsite)
• Salary: USD 229,900 - 262,400 per year
• Minimum experience: 2 years
• Education: Bachelor’s Degree

Responsibilities

• Design and deliver ML models and components that address real business needs, collaborating with Product and Data Science teams
• Guide ML infrastructure decisions by applying knowledge of modeling techniques, including model choice, data selection, feature engineering, training, hyperparameter tuning, dimensionality, bias versus variance, and validation
• Address complex problems by developing and testing application code, building validated 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 environments
• Leverage or construct cloud based architectures and platforms to deliver optimized ML models at scale
• Build optimized data pipelines to feed ML models
• Adopt continuous integration and continuous deployment practices, including test automation and monitoring, to ensure successful deployment
• Maintain well governed codebases to reduce vulnerabilities and ensure responsible and explainable AI practices
• Program using languages such as Python, Scala, or Java

Basic Qualifications

• 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 related field
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• 4+ years of practical experience with an industry recognized ML framework like scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 3+ years of writing performant, resilient, and maintainable code
• 3+ years of experience gathering and preparing data for ML models
• 3+ years of people management experience
• Impact in the ML field through conferences, publications, blog posts, open source work, or patents
• 3+ years building production ready data pipelines that feed ML models
• Ability to clearly communicate complex technical concepts to diverse audiences
• Experience leveraging interactive AI tooling to accelerate productivity beyond basic code completion

Technologies

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

Benefits

• Health benefits
• Financial benefits
• Performance-based incentive compensation, including cash bonuses and long term incentives