We are mainly looking for a ML Engineer who is experienced and ready to take on this role. The candidate should have a strong background in ML and be capable of handling the tasks and responsibilities that come with the position.

ML Infrastructure

Performance Engineer

Focus:

This role focuses on the "serving plane." The engineer will integrate high-speed inference runtimes with streaming loaders and take ownership of the performance benchmarking mandate.

Key Responsibilities:

Integrate

SGLang

with the

Run:ai Model Streamer

to enable concurrent tensor streaming directly to GPU memory, reducing model "cold start" times.

Optimize SGLang s backend runtime, leveraging features like

RadixAttention

for prefix caching and compressed finite-state machines for faster decoding.

Design and execute rigorous

performance benchmarking

suites to...