Product Manager II, ML Fleet Training

Define and execute the multi-year product roadmap for Google’s ML Training Fleet Efficiency across TPUs, targeting high-leverage bottlenecks and unlocking hundreds of millions in compute capacity. Standardize company-wide efficiency metrics (such as Prod System Duty Cycle/PSDC and PADC) and telemetry architectures to deliver actionable visibility across executive and engineering stakeholders. Partner with DeepMind and Core ML to optimize complex distributed training workloads, specifically targeting Reinforcement Learning, data ingestion pipelines, and check-pointing efficiency.

Drive the productization of "AI for AI" diagnostic platforms (e.g., agentic root-cause analysis and trace telemetry) to automate detractor resolution at fleet scale. Lead resource governance and quota frameworks across Search, Ads, Cloud, and GDM, fostering high-trust executive partnerships that maximize accelerator utilization without compromising research velocity.