ML Engineer 4: GenAI & Scalable AI on AWS

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

Job summary

Capital One is seeking a Machine Learning Engineer 4 to drive AI initiatives within Enterprise Platforms Technology. You will design, train, deploy, and monitor ML models at scale, collaborating with Product, Data Science, and Ops teams to solve real business problems.

The role emphasizes cloud architectures (AWS), Python/Java/Scala, and production-grade ML pipelines with GenAI exposure, big data tooling, and Responsible AI practices. On-site in McLean, VA with competitive compensation.

Qualifications

• Bachelor’s degree or higher in CS, ML or related quantitative field.
• 4+ years programming with Python, Java, Golang or C++.
• 4+ years ML experience using PyTorch or TensorFlow and libraries (Pandas, NumPy, Scikit-learn).
• 4+ years operating large-scale distributed systems (Spark, Ray).
• 2+ years deploying ML in production and cloud (AWS, GCP, Azure) with Kubernetes.

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Inform ML infrastructure decisions, including data, features, and training.
• Write and test application code, automate tests and deployment of models.
• Collaborate in a cross-functional Agile team to enable big data and ML apps.
• Retrain, maintain, and monitor models in production; ensure governance and responsible AI.

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

Kubernetes

CI/CD

ML pipelines

GenAI

Education

Bachelor’s degree in Computer Science or related quantitative field

Master’s degree (preferred)

Doctorate (advantageous)

Tools

AWS

Spark

Kubernetes

Cloud platforms

Job description

Capital One is seeking a Machine Learning Engineer 4 to drive AI initiatives within Enterprise Platforms Technology. You will design, train, deploy, and monitor ML models at scale, collaborating with Product, Data Science, and Ops teams to solve real business problems.

The role emphasizes cloud architectures (AWS), Python/Java/Scala, and production-grade ML pipelines with GenAI exposure, big data tooling, and Responsible AI practices. On-site in McLean, VA with competitive compensation.