Member of Technical Staff, Inference & RL Systems

Highlights

• Design and scale inference serving for long-context frontier models.
• Optimize throughput and latency under demanding KV-cache constraints.
• Power large-scale RL rollouts and post-training workflows in production.

What they offer

• Equity is a significant part of total compensation, in addition to salary
• 401(k) plan with 6% salary matching
• Generous health, dental and vision insurance for you and your dependents
• Unlimited paid time off
• Visa sponsorship and relocation stipend to bring you to SF, if possible

Ideal candidate

Systems-minded engineer who owns critical production infrastructure and thrives at the ML-systems boundary. You care about latency, reliability, and fast RL iteration for frontier models.

Requirements

• Strong software engineering and distributed systems fundamentals
• Experience building or operating large-scale inference or training systems
• Deep understanding of GPU execution constraints and memory trade-offs
• Experience debugging performance issues in production ML systems
• Ability to reason about system-level trade-offs between latency, throughput, and cost
• Track record of owning critical production infrastructure