Inferact

Member of Technical Staff, TPU Performance Engineering

San Francisco · Staff+

H1B sponsorship available$200k-$400kDetected 34 days ago

Machine LearningPyTorchLLMsLogistics

About the role

We're looking for a TPU performance engineer to make vLLM a first-class inference engine on Google TPUs.
You'll work at the boundary of inference systems, kernels, compilers, and hardware architecture, improving production-relevant model serving on TPU with clear correctness, latency, and throughput benchmarks.

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.
Your work will help make TPU support in vLLM usable, fast, benchmarked, and maintainable.

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.
Familiarity with batching, KV cache, decoding, serving tradeoffs, and backend performance constraints in production inference systems.
Experience with compiler technologies such as XLA, MLIR, LLVM, Pallas, or other kernel DSLs, including lowering, fusion, and backend code generation.
Knowledge of quantization methods such as INT8, FP8, mixed precision, or TPU-specific numeric formats, including accuracy and performance tradeoffs.
Contributed to vLLM, JAX/XLA, Pallas, PyTorch/XLA, compiler projects, or other open-source ML infrastructure.
Built TPU benchmarking infrastructure or automated performance regression detection for accelerator workloads.
Worked directly with Google TPU ecosystem stakeholders, accelerator platform teams, or early-access programs to ship backend, compiler, or inference performance improvements.
Visa sponsorship: We sponsor visas on a case-by-case basis.

Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.

Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.

Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster.
Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware, a position that took years to build.

This listing is sourced directly from Inferact's careers page and normalized into a canonical job model.