Senior Manager, Machine Learning Engineering

$234,700 - $267,900/Yr

Capital One - Cambridge, MA

Full-time - Senior

Cambridge, MA

Credit Intermediation and Related Activities

About the position

As a Senior Manager in Machine Learning Engineering at Capital One, you will lead an Agile team focused on the productionization of machine learning applications and systems at scale. This role involves the technical design, development, and implementation of machine learning solutions, ensuring high availability and performance while applying the latest innovations in the field.

Responsibilities

• Design, build, and deliver ML models and components that solve real-world business problems in collaboration with Product and Data Science teams.
• Inform ML infrastructure decisions using knowledge of ML modeling techniques, including model choice, data, feature selection, and validation.
• Solve 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 enhance software for big data and ML applications.
• Retrain, maintain, and monitor models in production.
• Leverage or build cloud-based architectures to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Implement continuous integration and continuous deployment best practices to ensure successful deployment of ML models and application code.
• Ensure code is well-managed to reduce vulnerabilities and that ML practices follow Responsible and Explainable AI guidelines.

Requirements

• Bachelor's degree
• At least 8 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 3 years of experience building, scaling, and optimizing ML systems
• At least 2 years of experience leading teams developing ML solutions
• At least 4 years of people management experience.

Nice-to-haves

• Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
• 4+ years of experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 3+ years of experience developing performant, resilient, and maintainable code
• 3+ years of experience with data gathering and preparation for ML models
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• 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
• ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents.

Benefits

• Comprehensive health insurance
• Financial benefits including performance-based incentives
• Support for total well-being
• Diversity and inclusion initiatives
• Paid time off and holidays