Senior Machine Learning Engineering Manager

Capital One; Richmond (VA); On-site; USD 209,000 - 239,000; Full time

Job summary

Capital One's Risk Tech team is seeking a Machine Learning Engineer to design, build, and deploy AI-powered risk management solutions. You will work closely with the GRC and Product teams to deliver scalable ML models and data pipelines that enhance risk prevention and detection across the business.

You’ll apply PyTorch/TensorFlow, Spark/Ray, and Kubernetes with cloud deployments (AWS/GCP/Azure) while advancing responsible AI practices in a fast-paced, collaborative environment.

Qualifications

• Bachelor's degree in Computer Science or related quantitative field.
• 6+ years of Python/Java/Golang/C++ experience.
• 6+ years ML experience with PyTorch or TensorFlow.
• 6+ years in large-scale distributed data processing (Spark, Ray).
• 4+ years deploying ML solutions in production in the cloud (AWS/GCP/Azure) and using Kubernetes.

Responsibilities

• Design, build, and deploy ML models and components solving real business problems with collaboration across Product and Data Science teams.
• Build and scale multi-tenant platforms for training and serving ML models at scale.
• Develop data pipelines to feed ML models and ensure monitoring and governance.

Job description

Capital One's Risk Tech team is seeking a Machine Learning Engineer to design, build, and deploy AI-powered risk management solutions. You will work closely with the GRC and Product teams to deliver scalable ML models and data pipelines that enhance risk prevention and detection across the business.

You’ll apply PyTorch/TensorFlow, Spark/Ray, and Kubernetes with cloud deployments (AWS/GCP/Azure) while advancing responsible AI practices in a fast-paced, collaborative environment.