The opportunity
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to…
What you'll do
Own New Platform Perception Evaluation strategy and coverage across: next-generation vehicle, sensing, and compute platforms
Lead product planning for New Platform Simrack capacity, demand forecasting,: and execution efficiency across compute generations, optimizing resource allocation and test coverage to shift-left timing, reliability, and fidelity Discovery and Validation
Define and execute the New Platform Introduction (NPI) Closed-Course: Rider-Only (CC-RO) structured testing strategy and roadmap, partnering with Systems Engineering to shake down new vehicle, hardware, and firmware configurations and accelerate RO issue discovery prior to public road deployment
Own RO Deployment ADC (RDA) as a product, defining the vision, requirements,: and roadmap for an RO-representative autonomous testing mode that exercises end-to-end depot automation loops (charging, auto PC, map updates), off-hail behaviors, long-duration engagement, fault policies, and fleet response (RAD/RS) before commercial launch
Drive NPI ADC Internal trip delivery, aligning NPI validation trip demand: with vehicle supply, fleet allocation, and Commercialization/Operations partners to surface rider UX (doors, windows, cabin controls) and driving quality issues early
Partner cross-functionally with Hardware, Systems Engineering, Firmware, and: Diagnostics teams to build a cohesive shift-left discovery and validation funnel (spanning HIL Simrack, Car-on-Bench, Closed-Course, RDA, and Internal trips) that compresses new platform bring-up timelines from prototype to commercial deployment
What they're looking for
- + years of product management or technical program/systems leadership: experience in autonomous vehicles, robotics, complex hardware-software systems, ML/perception evaluation, or large-scale testing and validation infrastructure
- Demonstrated track record of owning complex technical products: end-to-end—translating ambiguous system-level validation and operational challenges into clear product requirements, metrics, and multi-quarter roadmaps
- Strong analytical foundation in capacity and demand planning, resource: optimization, and operational efficiency for constrained hardware/compute test assets
- Deep systems thinking with the ability to reason across the full autonomous: stack—from sensors, compute, firmware, and base vehicle integration to perception/ML models, onboard software, and fleet operations
