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Job Description
- Architect data reconciliation frameworks to unify disparate datasets from multiple systems (e.g., resource symphony, allocation data, and fleet guidance), ensuring a single, high-fidelity source of truth for the ML fleet.
- Audit and resolve data discrepancies across cross-functional team inputs to maintain the integrity of fleet capacity and usage metrics.
- Develop and maintain complex investigative models that enable real-time, dynamic forecasting of ML fleet supply and demand, accounting for hardware transitions and shifting deployment timelines.
- Engineer automated dashboards that provide leadership with what-if scenario modeling to visualize the impact of divestments or increased GPU demand on the total fleet.
- Translate fleet capacity into actionable allocation plans for Product Areas (PAs), ensuring resource distribution aligns with Google’s ML priorities and commitments.