Software Engineer ML Infrastructure

You will improve the throughput and reliability of training, plan and build GPU infrastructure, scale compute environments for reinforcement-learning workloads, automate GPU-cluster operations, and build scheduling and data-movement systems.

Responsibilities

• Collaborate with ML researchers to improve training throughput and reliability
• Plan and build GPU infrastructure
• Improve compute-environment density and scalability for reinforcement-learning workloads
• Automate the building, monitoring, and operation of GPU clusters
• Build workload scheduling and data-movement systems

Requirements

• Systems and infrastructure software engineering
• Python
• TypeScript
• Rust
• Golang
• Distributed storage
• Networking infrastructure
• Linux
• Cloud infrastructure
• Bare-metal infrastructure
• Large-scale systems
• Infrastructure as code
• Configuration management
• Kubernetes