Senior Machine Learning Engineer - Scale Production AI

Capital One; Richmond (VA); On-site; USD 209,000 - 239,000; Full time

Benefits offered by this job

Competitive benefits

Performance-based incentives

Job summary

Capital One is seeking a Machine Learning Engineer to design, build, and scale ML models and big data applications in a fast-paced, collaborative environment. You’ll work with Product, Data Science, and Ops to deliver production-ready solutions and monitor models in production.

The role emphasizes scalable infrastructure, cloud platforms, and responsible AI practices, with opportunities for incentives and a competitive benefits package.

Qualifications

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

Responsibilities

• Design, build, and deliver ML models and components with Product and Data Science teams.
• Build and scale multi-tenant platforms for large-scale model training and serving.
• Select data, features, and models; train, tune, validate, and deploy ML solutions.
• Write robust code, test, and automate deployment and monitoring in production.
• Collaborate in an Agile team to enable state-of-the-art big data and ML apps.
• Retrain, maintain, and monitor models in production; ensure governance and risk controls.
• Leverage cloud architectures to optimize ML model performance and scale.

Skills

Python

Java

Golang

C++

PyTorch

TensorFlow

Spark

Kubernetes

Education

Bachelor's degree in Computer Science or related quantitative field

Tools

PyTorch

TensorFlow

Spark

Kubernetes

Job description

Capital One is seeking a Machine Learning Engineer to design, build, and scale ML models and big data applications in a fast-paced, collaborative environment. You’ll work with Product, Data Science, and Ops to deliver production-ready solutions and monitor models in production.

The role emphasizes scalable infrastructure, cloud platforms, and responsible AI practices, with opportunities for incentives and a competitive benefits package.