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Staff Software Engineer, Machine Learning, TPU Workload Optimization

Google· Google Singapore
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SingaporeFull-timePosted 2w ago

About the role

Senior software engineering role focused on onboarding, optimizing training and inference workloads on TPUs, delivering stable stack and reference models for large-scale ML training/inference on Google Cloud infrastructure.

Responsibilities

  • Act as ML software engineer leading the onboarding for stable stack, and optimization for training and serving solutions on the latest TPU NPIs.
  • Set the technical direction and architect the training/inference onboarding and optimization frameworks for our customer needs. Work closely with customers to onboard their workloads to production and optimization.
  • Collaborate with the ML research, ML performance, model optimization tooling, and other optimization teams.
  • Ship stable stack to our customers for training/inference optimization solutions on TPU.
  • Prepare and optimize very large reference models, demonstrating state of the art single-host and multi-host inference solutions, especially at large scale.

Qualifications

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 4 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • 2 years of experience with state of the art training (e.g. Megatron-LM, DeepSpeed) and inference techniques (e.g. TensorRT-LLM, vLLM, SGLang).

Skills

Required:Software developmentML design and ML infrastructure optimizationState of the art training and inference techniques
Last updated Oct 23, 2026. Interested? Apply on the company site.

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