Senior ML Engineer — Production AI at Scale

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

Job summary

Capital One in Wilmington, DE is hiring a Machine Learning Engineer 4 to design, build, and deploy production ML models at scale. You will work with product, data science, and operations teams in an agile environment to solve real business problems using Python, Java, and modern ML frameworks.

This role emphasizes cloud deployment (AWS/GCP/Azure), distributed data systems (Spark, Ray), CI/CD, and governance of responsible AI practices.

Qualifications

• Bachelor's degree in Computer Science, ML or related quantitative field.
• At least 4 years of experience with Python/Java/Golang/C++ and ML using PyTorch or TensorFlow.
• At least 4 years operating large-scale distributed systems (Spark, Ray).
• At least 2 years deploying ML in production on cloud and using Kubernetes.

Responsibilities

• Design, build, and deliver ML models and components that solve real-world business problems with Product and Data Science teams.
• Inform infrastructure decisions using modeling techniques, data, feature selection, and model training.
• Write production code, validate models, and automate tests and deployment.
• Collaborate in a cross-functional Agile team to create scalable ML applications.
• Retrain, monitor, and maintain models in production.
• Leverage cloud architectures to deliver optimized ML models at scale.
• Construct data pipelines to feed ML models and ensure CI/CD with monitoring.
• Ensure governance and Responsible AI practices in code and models.

Skills

Python

Java

Golang

C++

Education

Bachelor's degree in CS/ML or related field

Master's or PhD preferred

Tools

PyTorch

TensorFlow

Spark

Ray

Kubernetes

AWS

GCP

Azure

Job description

Capital One in Wilmington, DE is hiring a Machine Learning Engineer 4 to design, build, and deploy production ML models at scale. You will work with product, data science, and operations teams in an agile environment to solve real business problems using Python, Java, and modern ML frameworks.

This role emphasizes cloud deployment (AWS/GCP/Azure), distributed data systems (Spark, Ray), CI/CD, and governance of responsible AI practices.