Senior/Lead AI/ML Performance Engineer

Job description

We are looking for a Senior/Lead AI/ML Performance Engineer to benchmark and profile AI/ML workloads on TPU hardware to generate the empirical performance data that feeds the optimization solver's cost model.

Responsibilities

- Conduct JAX/XLA benchmarking on physical TPU slices

- Capture and analyze TPU Profiler traces

- Build hardware coefficient matrices for use in the optimizer's cost model

- Profile LLM training/inference performance (FLOPS, memory access, token throughput)

- Collaborate with Optimization Engineers to calibrate solver inputs

Requirements

- Strong understanding of the modern AI/ML landscape and LLM architectures

- Hands-on experience with LLM models/pipelines (training and inference)

- Proficiency in Python and/or Golang

- Familiarity with TensorFlow, PyTorch, and LangChain

- Experience with JAX/XLA and TPU-specific profiling tools

Nice to have

- Experience with GPU/TPU performance benchmarking at scale

- Background in ML systems or MLPerf-style benchmarking