Requirements

Strong programming skills in Go, or other similar languages
Strong systems engineering background: distributed systems, schedulers, control planes, or high-throughput data planes
Production experience with Kubernetes internals — controllers, informers, operators — not just deploying to it
Bias toward observability and debuggability: building a system that is easy to navigate when debugging production issues
Experience in systems serving large scale inference requests (preferred)

What You'll Be Doing

Design and develop internal scheduling system to maximize GPU utilization
Build API and tooling to help manage the lifecycle of GPU workloads and troubleshoot failures
Design and improve inference control plane to speed up model deployment and inference request serving
Collaborate with research to improve research velocity continuously