Member of Technical Staff, GPU & Distributed Systems

Highlights

• Build distributed systems that run real-time world models at scale.
• Cut model cold starts from minutes to seconds for live sessions.
• Improve fleet efficiency and tail latency across GPU clouds.

Ideal candidate

Systems-minded engineer with production distributed systems experience who loves deep performance work and owns projects from design through benchmarking to production.

Requirements

• 3+ years building distributed systems, cloud platforms, or performance-sensitive systems software in production
• Strong programming skills in Go, Rust, C++, or Python with concurrency and resource management
• Hands-on GPU or ML systems experience such as model loading, accelerator memory, distributed execution or inference serving
• Strong Linux, networking, and storage fundamentals with performance diagnosis across hardware and software
• Experience extending Kubernetes via controllers, operators, or scheduling plugins or comparable orchestration
• Ability to reason about partial failures, resource contention, and latency-throughput tradeoffs