Sr. Staff Systems Engineer, Perception-Planner Risk
Waymo · Mountain View, CA, US
About this role
## Waymo — Sr. Staff Systems Engineer, Perception-Planner Risk Waymo is an autonomous driving technology company on a mission to be the world’s most trusted driver. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and is built on extensive real-world and simulation experience. Waymo’s Systems Engineering team blends software and hardware systems, sets performance standards to keep passengers safe, and designs/executes tests that validate that performance. ### You will - Define the approach for **quantitative safety risk analysis** across sensing and perception systems engineering, building on Waymo-wide risk assessment and management methodologies. - Design, develop, and implement **quantitative methods and statistical models** to evaluate **end-to-end performance** for current and counterfactual sensor suites. - Apply the approach to **rare events** and scenarios with scarce operational data (e.g., interacting with pedestrian crowds, navigating around floods, degraded sensing in construction zones). - Develop and prototype novel workflows to: - Determine required performance levels for sensing and perception tasks - Support trade studies informing perception architecture decisions (hardware/software) - Estimate exposure of events relevant to perception-driven behavioral risk - Improve quantitative rigor, standardization, execution efficiency, and reporting of end-to-end risk from V&V outcomes in complex contexts - Expand methodologies needed to enter new operational design domains and address emergent challenges. - Collaborate closely with: - **Onboard Software and Evaluation** (mapping perception/planner evaluation to end-to-end risk in large models) - **Test Engineering** (cross-calibrating risk from V&V results across methodologies/coverage; improving test tooling across public roads/closed course tests and logged/synthetic scenarios) - **Systems Safety** (allocating quantitative risk across functional insufficiencies) - Communicate complex quantitative findings and recommendations to diverse stakeholders, including senior leadership, to enable safety at scale. ### You have - Bachelor’s degree or higher in **computer science, math, physics, engineering, or related field** - **10+ years** of engineering experience delivering high-stakes technical roadmaps that resolved architectural friction and deployed business-critical systems - Experience using **AI productivity tools** for analysis and workflow development - Proficiency and experience in: - Vehicular robotics (development or evaluation) - Software development (**Python or C++**) - Statistical or predictive modeling - Experimental design and developing metrics for quantitative methods - Deep technical knowledge of at least two of: - State-of-the-art ML techniques powering modern perception systems and large end-to-end models - Quantitative risk estimation using simulators (preferably sensors-in-loop) - Systems engineering fundamentals (requirements definition, formal verification/validation) - Track record leading complex projects in safety-critical applications with leadership-facing accountability across software, operations, data science, product, and testing - Excellent verbal and written communication skills; ability to manage by influence ### We prefer - Master’s (with thesis) or PhD in **machine learning, statistics, robotics, or related quantitative field** - Autonomy driving industry experience - Experience testing on la
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