Member of Technical Staff - Distributed Systems

Sail Research•San Francisco, CA

7d•Onsite

About The Position

Sail is the foundation of useful, agentic AI. We are here to take a big swing at the most ambitious engineering challenge of our careers. Everyone working at Sail will become an expert; nothing less will do in our immensely competitive market. Build the systems that make AI inference fast, reliable, and cost-efficient at global scale. You’ll design the control plane that schedules and autoscales our enormous queue of tokens over a diverse fleet of machines, spread all over the world.

Requirements

Strong distributed systems fundamentals (concurrency, networking, databases, queues, performance engineering).
Eagerness to work with agents coupled with a healthy dose of skepticism.
We start by focusing our attention on the highest-level design decisions first, and try to debate and justify each of decisions.
Then, we use our finite review time on the critical pieces of the system that we must build good mental models of to do good work.

Nice To Haves

experience with ML inference stacks (vLLM/SGLang), GPUs/accelerators, high-RPS systems (e.g. trading, messaging)

Responsibilities

Design and implement high-performance schedulers (admission control, queuing, priority, fairness, preemption, bin packing).
Build global routing and traffic management (latency-aware dispatch, predictive autoscaling, failover strategies, cache-aware routing).
LLM-specific routing optimizations, e.g. KV caching that lets us trade memory for compute, across the cascading layers of GPU RAM, CPU RAM, and NVMe flash.
Build deep observability: we want to trace every millisecond of our systems, and catch failures early enough that we can make things right before customers even notice.