Job description

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 mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo’s Product Management Team is a mission-driven team responsible for writing and enacting first-of-their-kind playbooks to bring fully autonomous driving technology to market. Our team develops simple solutions for complex problems by orchestrating cross-functional efforts to safely drive Waymo’s technology and the products it enables forward. We do this by understanding the customer, the business, and the technology. We are humble about the scope of our work, collaborative in our approach to problem-solving, and ambitious about our vision for the future. This role follows a hybrid work schedule and reports to the Product Management Lead of New Platform Introductions (NPI) . You will: 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 You have: 7+ 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 Proven ability to influence and align diverse cross-functional stakeholders across Engineering (Onboard SW, Simulation, Hardware), Systems Engineering, Testing Operations, and Commercialization without direct authority BS/MS in Computer Science, Electrical/Mechanical/Robotics Engineering, Systems Engineering, or a related technical field, or equivalent practical experience We prefer: Direct experience with New Platform Introduction (NPI), vehicle/hardware bring-up, or transitioning autonomous/robotics platforms from prototype validation to commercial rider-only deployment Experience with autonomous driving perception and ML model evaluation methodologies Hands-on familiarity with Hardware-in-the-Loop (HIL) simulation, Car-on-Bench (COB) testing, closed-course structured testing, and public road autonomous fleet validation workflows Experience designing and scaling Internal testing programs, operational readiness frameworks, or production-representative testing environments for autonomous fleets Experience building S&OP (Supply & Operations Planning) or demand/supply matching processes for physical test fleets, depot operations, or hardware testbeds Comfort operating in a fast-paced, multi-platform environment with simultaneous hardware, compute, and software generations in flight Travel requirements: Occasional travel (up to 10%) between Bay Area offices (Mountain View, San Francisco), depots, and closed-course testing facilities (AZ, CA) as needed for platform validation milestones. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $241,000 — $297,000 USD

Requirements

Must-haves

This role follows a hybrid work schedule and reports to the Product Management Lead of New Platform Introductions (NPI) .
Own New Platform Perception Evaluation strategy and coverage across next-generation vehicle, sensing, and compute platforms
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
Proven ability to influence and align diverse cross-functional stakeholders across Engineering (Onboard SW, Simulation, Hardware), Systems Engineering, Testing Operations, and Commercialization without direct authority
BS/MS in Computer Science, Electrical/Mechanical/Robotics Engineering, Systems Engineering, or a related technical field, or equivalent practical experience
Direct experience with New Platform Introduction (NPI), vehicle/hardware bring-up, or transitioning autonomous/robotics platforms from prototype validation to commercial rider-only deployment
Experience with autonomous driving perception and ML model evaluation methodologies
Hands-on familiarity with Hardware-in-the-Loop (HIL) simulation, Car-on-Bench (COB) testing, closed-course structured testing, and public road autonomous fleet validation workflows
Experience designing and scaling Internal testing programs, operational readiness frameworks, or production-representative testing environments for autonomous fleets
Experience building S&OP (Supply & Operations Planning) or demand/supply matching processes for physical test fleets, depot operations, or hardware testbeds
Comfort operating in a fast-paced, multi-platform environment with simultaneous hardware, compute, and software generations in flight
Occasional travel (up to 10%) between Bay Area offices (Mountain View, San Francisco), depots, and closed-course testing facilities (AZ, CA) as needed for platform validation milestones.

Nice-to-haves

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Platform: greenhouse
Effort: quick

Benefits

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