Senior Manager, Machine Learning Engineering - Capital One Software (Remote)

$198,900 - $227,000/Yr

Capital One - McLean, VA

Full-time - Senior

Remote - McLean, VA

Credit Intermediation and Related Activities

About the position

As a Senior Manager in Machine Learning Engineering at Capital One, you will lead a team focused on building and delivering machine learning models and components that address real-world business challenges. This role involves collaboration with product and data science teams, overseeing the development of ML systems, and ensuring best practices in model governance and deployment. You will play a crucial role in shaping the future of Capital One Software by leveraging cloud-based technologies and optimizing data pipelines for scalable ML applications.

Responsibilities

• Design, build, and deliver ML models and components that solve real-world business problems.
• Collaborate with Product and Data Science teams to inform ML infrastructure decisions.
• Write and test application code, develop and validate ML models, and automate tests and deployment.
• Work as part of 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 for ML models and application code.
• Ensure code is well-managed to reduce vulnerabilities and models are well-governed from a risk perspective.

Requirements

• Bachelor's degree in a relevant field.
• 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 coverage.
• Financial benefits including performance-based incentives and bonuses.
• Support for total well-being through various programs.