Senior ML Engineer: Build Production-Grade AI at Scale

Capital One; McLean (VA); On-site; USD 230,000 - 262,000; Full time

Job summary

Capital One seeks a Machine Learning Engineer to design and deploy ML models and scalable data pipelines in a fast-paced, collaborative setting. You will work with product and data science teams to deliver production-ready ML products and responsible AI practices.

You will build multi-tenant platforms, train and serve models at scale, and leverage cloud architectures (AWS/GCP/Azure) with Kubernetes. Strong Python/Java/Golang/C++ and PyTorch/TensorFlow skills are required.

Qualifications

• Bachelor's degree or higher in Computer Science, ML or related quantitative field
• 6+ years programming in Python, Java, Golang or C++
• 6+ years ML experience with PyTorch or TensorFlow and libraries
• 6+ years operating large-scale distributed systems (Spark, Ray)
• 4+ years deploying ML solutions in production in the cloud (AWS, GCP, Azure) and Kubernetes use

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams
• Scale multi-tenant platforms for training and serving ML models at scale
• Inform infrastructure decisions with ML modeling techniques and data choices
• Write/validate code, build models, and automate tests and deployment
• Collaborate in an Agile cross-functional team to enable advanced ML apps
• Retrain, monitor, and maintain models in production
• Construct data pipelines feeding ML models and leverage CI/CD

Skills

Python

Java

Golang

C++

ML engineering

Education

Bachelor's degree in CS or quantitative field

Tools

PyTorch

TensorFlow

Spark

Ray

Kubernetes

Job description

Capital One seeks a Machine Learning Engineer to design and deploy ML models and scalable data pipelines in a fast-paced, collaborative setting. You will work with product and data science teams to deliver production-ready ML products and responsible AI practices.

You will build multi-tenant platforms, train and serve models at scale, and leverage cloud architectures (AWS/GCP/Azure) with Kubernetes. Strong Python/Java/Golang/C++ and PyTorch/TensorFlow skills are required.