Platform Engineer, MLOps

Overview

Role focused on building and maintaining infrastructure for AI/ML development and production.

Ideal candidate should have 5+ years of experience in managing core infrastructure for large-scale systems.

Locations

• United States, California, San Francisco

Requirements

• 5+ years experience in infrastructure
• Deep experience with Kubernetes and Docker
• Expertise in cloud platforms (GCP, AWS, Azure)
• Proficiency in Python and Bash scripting
• Familiarity with ML frameworks like PyTorch
• Experience with monitoring tools like Prometheus

Responsibilities

• Develop and manage CI/CD pipelines
• Set up and monitor logging and observability systems
• Operate and optimize Kubernetes clusters
• Manage containerization using Docker
• Ensure high availability of training environments
• Support MLOps infrastructure performance
• Troubleshoot complex systems

Benefits

• Generous paid time off
• Comprehensive medical, dental, and vision insurance
• 12 weeks paid parental leave
• Fertility and family planning support
• Flexible spending accounts
• Annual stipends for home office setup
• Competitive salary and stock options
• 401(k) plan