ML Performance Engineering Manager (TPU & Optimization)

Google; Sunnyvale (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google’s Core Machine Learning (ML) team seeks an Engineering Manager to lead TPU Performance initiatives. You will guide teams across ML training and serving benchmarks, driving performance for Google production and OSS models.

You’ll align model deployment strategies with hardware-aware optimizations and scale engineering programs globally. You will mentor engineers, shape project goals, and partner with cross‑functional groups to push innovations in AI hardware and software ecosystems,

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.
• Experience with ML performance analysis, benchmarking, and computer architecture.

Responsibilities

• Lead a team of software engineers focused on identifying and maintaining ML training and serving benchmarks that are representative to Google production and the broader ML industry.
• Achieve performance for customer launches, and in case of third-party/open-source software (OSS) models, for engaged benchmark submissions (ML Commons, InferenceX, etc.).
• Use benchmarks to identify performance opportunities and drive both near‑term SOTA (e.g., custom kernels) and out‑of the box performance (compiler/runtime optimizations, agentic tooling, auto‑sharding) directly and in collaboration with partner teams.
• Participate in algorithmic innovations exploiting new TPU hardware features and model‑preserving optimizations (speculative decoding, sparsity, quantization, LoRA, etc.).
• Participate in co‑designing models that are TPU‑friendly to showcase model quality at performance advanced to OSS models typically designed on GPUs.

Skills

Strategic ML leadership

Software development

ML performance analysis

Benchmarking

Team leadership

Model deployment

Debugging & tuning

Computer architecture

Education

Bachelor's degree or equivalent

Master’s or PhD in Engineering/CS

Tools

CUDA

Triton

Pallas

MLIR

OpenXLA

PyTorch

JAX

vLLM

Job description

Google’s Core Machine Learning (ML) team seeks an Engineering Manager to lead TPU Performance initiatives. You will guide teams across ML training and serving benchmarks, driving performance for Google production and OSS models.

You’ll align model deployment strategies with hardware-aware optimizations and scale engineering programs globally. You will mentor engineers, shape project goals, and partner with cross‑functional groups to push innovations in AI hardware and software ecosystems,