Member of Technical Staff, Infrastructure Engineer

The role

This person will develop and operate a low-latency model inference platform and scale core data processing infrastructure. They will design and maintain large-scale GPU-based training clusters for deep learning.

What you will do

• Develop and operate low-latency model inference platform
• Engineer and scale core data processing infrastructure
• Design, build, and maintain large-scale, GPU-based training clusters
• Automate infrastructure provisioning, configuration, monitoring, and alerting using Infrastructure as Code
• Drive performance tuning, cost optimization, and reliability improvements
• Collaborate with researchers and product developers to optimize workflows and platform usability

Required qualifications

• Strong programming skills (e.g., Python, Go, or similar)
• Solid understanding of software engineering best practices
• Deep, hands-on experience with containerization (e.g., Docker)
• Experience with container orchestration (Kubernetes)
• Experience with Infrastructure as Code (Terraform)
• Proven experience building and managing large-scale, distributed systems with GPU computational workloads
• Experienced in designing infrastructure for ML workloads where performance, parallelism, and data movement are critical
• Collaborative mindset
• Excellent communication skills

About the company

Odyssey is an AI lab pioneering general world models. The founders previously pioneered self-driving cars and have brought together a research team from DeepMind, Tesla, Waymo, Meta, Apple, and Wayve.