Member of Technical Staff, Performance and Scale

We're looking for an infrastructure engineer to build the distributed systems that power inference at global scale. You'll design and implement the foundational layers that enable vLLM to serve models across thousands of accelerators with minimal latency and maximum reliability. Tomorrow, deploying a frontier model at scale should be as straightforward as spinning up a serverless database. The complexity doesn't disappear as it gets absorbed into the infrastructure you're building.

Minimum qualifications: Bachelor's degree or equivalent experience in computer science, engineering, or similar. Strong systems programming skills in Rust, Go, or C++. Experience designing and building high-performance distributed systems at scale. Understanding of network protocols and high-performance I/O. Ability to debug complex distributed systems issues. Preferred qualifications: Experience with ML serving infrastructure and disaggregated inference architecture. Familiarity with GPU memory