Member of Engineering (Compute)
Remote
Job Summary
Design and develop internal scheduling systems to maximize GPU utilization across the company. Build APIs and tooling to manage GPU workload lifecycles and troubleshoot failures. Improve the inference control plane to accelerate model deployment and request serving. Collaborate with research, scalability, and infrastructure teams to stabilize large-scale fault-tolerant training and ensure full node utilization. Optimize GPU utilization and deliver a stable, scalable inference serving stack for researchers. This role supports the compute team's mission to improve research velocity and enable frontier model development through intelligence systems built for software development.
Required Qualifications
- 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
Desired Qualifications
- Plus: experience in systems serving large scale inference requests
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