Act as ML software engineer leading the onboarding for stable stack, and optimization for training and serving solutions on the latest TPU NPIs. Work closely with customers to onboard their workloads to production and optimization. Work on the technical details and architect the training/inference onboarding and optimization frameworks for our customer needs. 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 SOTA single-host and multi-host inference solutions, especially at large scale.
Job description provided by Google.
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