Member of Technical Staff, Inference
Inferact, San Francisco
The role
We're looking for an inference runtime engineer to push the boundaries of what's possible in LLM and diffusion model serving. Models grow larger. Architectures shift: mixture-of-experts, multimodal, agentic. Every breakthrough demands innovations on the inference engine itself. You'll work at the core of vLLM, optimizing how models execute across diverse hardware and architectures. Your work will directly impact how the world runs AI inference.
What you need
- Bachelor's degree or equivalent experience in computer science, engineering, or similar.
- Deep understanding of transformer architectures and their variants.
- Strong programming skills in Python with experience in PyTorch internals.
- Experience with LLM inference systems (vLLM, TensorRT-LLM, SGLang, TGI).
- Ability to read and implement model architectures and inference techniques from research papers.
- Demonstrate the ability to contribute performant and maintainable code and debug in complex ML codebases.