Hybrid Lead Machine Learning Engineer – Enterprise Platforms Technology

at Capital One

• Job title: Lead Machine Learning Engineer – Enterprise Platforms Technology
• Job type: Full Time
• Experience level: Senior
• Salary: $197,300 - $225,100 per year
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Google Cloud Platform, Java, Python, PyTorch, Scala, Scikit-Learn, Spark, Tensorflow
• Location requirements: Hybrid, McLean, United States

About the role

• Machine Learning Engineer at Capital One responsible for productionizing ML applications in Agile teams. Focused on ML architectural design, coding, and maintaining high availability of models.

Responsibilities

• Participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms
• Focus on machine learning architectural design and development
• Review model and application code
• Ensure high availability and performance of machine learning applications
• Continuously learn and apply latest innovations and best practices in machine learning engineering
• Design, build, and/or deliver ML models and components that solve real-world business problems
• Inform ML infrastructure decisions using understanding of ML modeling techniques and issues
• Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment
• Collaborate as part of a cross-functional Agile team
• 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
• Leverage continuous integration and continuous deployment best practices, including test automation and monitoring

Requirements

• Bachelor’s Degree
• At least 6 years of experience designing and building data-intensive solutions using distributed computing
• At least 4 years of experience programming with Python, Scala, or Java
• At least 2 years of experience building, scaling, and optimizing ML systems
• Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field (preferred)
• 3+ years of experience building production-ready data pipelines that feed ML models (preferred)
• 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow (preferred)
• 2+ years of experience developing performant, resilient, and maintainable code (preferred)
• 2+ years of experience with data gathering and preparation for ML models (preferred)
• 2+ years of people leader experience (preferred)
• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation (preferred)
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform (preferred)
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance (preferred)

Benefits

• Comprehensive health benefits
• Performance based incentive compensation
• Cash bonuses and/or long term incentives (LTI)