Optimizing ML infrastructure jobs

Staff Software Engineer, Machine Learning, TPU Workload Optimization

Google · Posted Nov 10, 2026

Lead ML software engineering for TPU training and inference optimization

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.

Bachelor’s degree or equivalent practical experience
Nice to have: Master’s degree or PhD in Engineering, Computer Science, or a related technical field
Nice to have: optimizing machine learning models for large scale training/inference workloads
Nice to have: large scale ML optimizations techniques for improving latency and throughput
Nice to have: experience with accelerators (TPUs or GPUs) or HPC