Senior ML Engineer - Production AI at Scale

Capital One; McLean (VA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One is seeking a Machine Learning Engineer 4 (IC) in McLean, VA to design, build, and scale ML solutions that solve real business problems. You’ll work with Product and Data Science teams in an Agile environment, delivering production-ready models and data pipelines at scale.

You’ll apply cutting-edge frameworks (PyTorch/TensorFlow) and cloud platforms (AWS, GCP, Azure), write robust code, and mentor junior engineers while adhering to responsible AI practices.

Qualifications

• Bachelor's degree or higher in CS or a related quantitative field.
• 4+ years Python/Java/Golang/C++ and 4+ years ML with PyTorch or TensorFlow.
• 4+ years building and operating large-scale distributed systems (Spark, Ray).
• 2+ years deploying ML in production on cloud platforms with Kubernetes.

Responsibilities

• Design, build, and deliver ML models that solve business problems with Product and Data Science teams.
• Inform infrastructure decisions with modeling techniques, data, features, and validation.
• Write and test application code, train models, and automate tests and deployment.
• Collaborate in a cross-functional Agile team to enable scalable ML apps.
• Retrain, maintain, and monitor models in production.
• Leverage cloud architectures to deliver optimized ML models at scale.
• Construct data pipelines to feed ML models.
• Apply CI/CD, test automation, and monitoring for reliable deployments.
• Ensure code governance and responsible/Explainable AI practices.

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Spark

Ray

Kubernetes

Education

Bachelor's degree in CS/ML

Master's degree

Tools

Spark

Ray

Kubernetes

AWS

GCP

Azure

Job description

Capital One is seeking a Machine Learning Engineer 4 (IC) in McLean, VA to design, build, and scale ML solutions that solve real business problems. You’ll work with Product and Data Science teams in an Agile environment, delivering production-ready models and data pipelines at scale.

You’ll apply cutting-edge frameworks (PyTorch/TensorFlow) and cloud platforms (AWS, GCP, Azure), write robust code, and mentor junior engineers while adhering to responsible AI practices.