Senior ML Engineer 4: AI at Scale on AWS & Python

Capital One Group; McLean (VA); Hybrid; USD 197,000 - 225,000; Full time

Job summary

Capital One is seeking a Machine Learning Engineer 4 to design, build, and deploy ML models at scale on AWS within the Enterprise Platforms Technology group. You’ll work across ML engineering, data science, and data engineering, delivering production-grade models, data pipelines, and scalable ML solutions in a collaborative Agile environment.

The role requires 4+ years in ML with PyTorch/TensorFlow, strong programming skills (Python/Java/C++), and hands-on cloud and distributed systems

Qualifications

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

Responsibilities

• Design, build, and deliver ML models and components that solve real-world business problems, collaborating with Product and Data Science teams.
• Inform ML infrastructure decisions with modeling techniques, data, features, and validation.
• Retrain, maintain, and monitor models in production and automate tests and deployment.
• Construct optimized data pipelines to feed ML models and use CI/CD for deployment.
• Ensure code quality, governance, and Responsible/Explainable AI practices.

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Spark

Ray

AWS

Education

Bachelor’s degree in CS or related field

Master’s or PhD in CS/EE/Math

Tools

Pandas

NumPy

Scikit-learn

Job description

Capital One is seeking a Machine Learning Engineer 4 to design, build, and deploy ML models at scale on AWS within the Enterprise Platforms Technology group. You’ll work across ML engineering, data science, and data engineering, delivering production-grade models, data pipelines, and scalable ML solutions in a collaborative Agile environment.

The role requires 4+ years in ML with PyTorch/TensorFlow, strong programming skills (Python/Java/C++), and hands-on cloud and distributed systems