# Member of Technical Staff, TPU Performance Engineering at Inferact

- Company: Inferact
- What the company does: Inferact is a startup founded by creators and core maintainers of vLLM, the most popular open-source LLM inference engine. Our mission is to grow vLLM as the world. Backed by Sequoia and Redpoint.
- Company website: https://inferact.ai/
- Type: Startups (AI role)
- Level: Senior
- Location: San Francisco
- Work setup: On-site
- Pay: $200K to $400K base salary per year (USD)
- Posted: 2026-06-17
- Apply by: 2026-10-08
- Apply: https://jobs.ashbyhq.com/inferact/24ea1266-bc29-4838-9a61-8adc1d5bb2c6
- Page: https://www.1752.vc/careers/jobs/inferact-member-of-technical-staff-tpu-performance-engineering/

## About the role

We're looking for a TPU performance engineer to make vLLM a first-class inference engine on Google TPUs. You'll build and optimize TPU backends, compiler integrations, runtime paths, and benchmarking infrastructure using JAX, XLA, Pallas, and related tooling so vLLM can deliver frontier inference performance on TPU hardware.

## What they're looking for

- Bachelor's degree or equivalent experience in computer science, engineering, systems, machine learning, or similar
- Hands-on experience building or optimizing TPU workloads using JAX, XLA, Pallas, or related compiler and runtime tooling
- Deep understanding of TPU execution, memory behavior, compilation, and performance constraints for ML workloads
- Experience optimizing ML kernels or inference paths such as attention, GEMM, sampling, KV cache, fused kernels, or backend runtime paths
- Strong performance profiling and benchmarking skills, with the ability to use measurements, compiler artifacts, correctness tests, and reproducible benchmarks to guide optimization work
- Experience with vLLM, SGLang, TensorRT-LLM, XLA-based serving, or other LLM inference systems

Tags: Research & Engineering