Lead Machine Learning Engineer - Capital One Software (Remote)

$170,700 - $194,800/Yr

Capital One

Full-time - Senior

Remote

Credit Intermediation and Related Activities

About the position

As a Lead Machine Learning Engineer at Capital One, you will play a pivotal role in building and delivering machine learning models and components that address real-world business challenges. This position involves collaboration with product and data science teams, focusing on the design, development, and optimization of ML systems. You will also be responsible for maintaining and monitoring models in production, leveraging cloud-based architectures, and ensuring best practices in responsible AI.

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 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.

Nice-to-haves

• Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
• 3+ years of experience building production-ready data pipelines that feed ML models.
• 3+ years of experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow.
• 2+ years of experience developing performant, resilient, and maintainable code.
• 2+ years of experience with data gathering and preparation for ML models.
• 2+ years of people leader experience.
• 1+ years of experience leading teams developing ML solutions using industry best practices.

Benefits

• Comprehensive health insurance coverage.
• Financial benefits including performance-based incentives and bonuses.
• Support for total well-being through various programs.