Machine Learning Engineer - Foundations & Production

Capital One Group; McLean (VA); On-site; USD 179,000 - 205,000; Full time

Job summary

Capital One is seeking a Machine Learning Engineer 4 to drive ML modeling, productionization, and large-scale data pipelines. You will collaborate withProduct and Data Science teams, build scalable ML components, and deploy across cloud platforms using Kubernetes and modern CI/CD practices.

The role emphasizes responsible AI, model governance, and scalable production systems, with opportunities to lead ML solutions and influence architecture in a fast-paced environment.

Qualifications

• Bachelor's degree or higher in CS, ML or related quantitative field.
• 4+ years of Python/Java/Golang/C++ programming experience.
• 4+ years of ML experience with PyTorch or TensorFlow.
• 4+ years operating large-scale distributed systems (Spark, Ray).
• 2+ years deploying ML in production on cloud (AWS, GCP, Azure) and using Kubernetes.
• Master's/Doctoral degree in CS/EE/Math or related preferred.
• 3+ years optimizing ML algorithms and following CI/CD best practices.

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Inform ML infrastructure decisions, including model choice, data, and feature selection.
• Write and test application code, develop and validate ML models, and automate tests and deployment.
• Collaborate in a cross-functional Agile team to create software for big data and ML apps.
• Retrain, maintain, and monitor models in production.
• Leverage cloud architectures to deliver optimized ML models at scale.
• Construct optimized data pipelines to feed ML models.
• Apply CI/CD and monitoring to ensure reliable deployment and governance.

Skills

Python

Java

Golang

C++

Education

Bachelor's degree or higher in CS/ML or related field

Master's or Doctoral degree in CS/EE/Math or related field

Tools

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

Kubernetes

CI/CD

Job description

Capital One is seeking a Machine Learning Engineer 4 to drive ML modeling, productionization, and large-scale data pipelines. You will collaborate withProduct and Data Science teams, build scalable ML components, and deploy across cloud platforms using Kubernetes and modern CI/CD practices.

The role emphasizes responsible AI, model governance, and scalable production systems, with opportunities to lead ML solutions and influence architecture in a fast-paced environment.