Senior MLOps Engineer

Overview

Role involves deploying and managing scalable ML services and optimizing infrastructure.

Ideal candidate has 5+ years in MLOps with strong Kubernetes and GPU optimization skills.

Locations

• United States

Requirements

• Degree in Computer Science or related field
• Proficiency in Kubernetes and containerization
• Experience with GPU optimization and cloud platforms

Responsibilities

• Deploy scalable ML services
• Optimize GPU resources
• Manage cloud storage
• Integrate ML techniques
• Set up monitoring solutions
• Write CI/CD pipelines
• Automate workflows