Senior ML Engineer — Scale Production Models in the Cloud

COMFORT SYSTEMS; Richmond (VA); On-site; USD 209,000 - 239,000; Full time

Job summary

Capital One in Richmond, VA is seeking a Machine Learning Engineer 5 to design, deploy, and scale ML models for production. You will work with product, data science, and ops teams to deliver robust AI solutions in a collaborative environment.

The role requires strong Python/Java/Golang/C++ skills, experience with PyTorch/TensorFlow, and production-grade ML pipelines on cloud platforms with Kubernetes.

Qualifications

• Bachelor's degree or higher in CS, ML or related quantitative field.
• 6+ years programming with 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 on cloud and using Kubernetes.

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 ML infra decisions: model choice, data, features, and validation.
• Write production code, validate ML models, and automate tests and deployment.
• Collaborate in an Agile team to build state-of-the-art big data/ML apps.
• Retrain, maintain, and monitor models in production.
• Leverage cloud architectures to deliver optimized ML models at scale.

Skills

Python

Java

Golang

C++

ML engineering

Distributed systems

Education

Bachelor's degree in CS or related field

Master's degree (preferred)

Tools

PyTorch

TensorFlow

Pandas

NumPy

Scikit-learn

Spark

Ray

Kubernetes

AWS

GCP

Azure

Job description

Capital One in Richmond, VA is seeking a Machine Learning Engineer 5 to design, deploy, and scale ML models for production. You will work with product, data science, and ops teams to deliver robust AI solutions in a collaborative environment.

The role requires strong Python/Java/Golang/C++ skills, experience with PyTorch/TensorFlow, and production-grade ML pipelines on cloud platforms with Kubernetes.