Sr. Staff Systems Engineer, Perception-Planner Risk
About The Position
Waymo is an autonomous driving technology company focused on building the Waymo Driver, which powers its autonomous ride-hail service and can be applied to other vehicle platforms and product use cases. The Systems Engineering team combines software and hardware systems, sets performance standards, and designs and performs tests to validate vehicle performance and passenger safety. The Sr. Staff Systems Engineer, Perception-Planner Risk will define and apply quantitative safety risk analysis approaches for sensing and perception systems engineering, building on Waymo-wide risk assessment and management methodologies. The role involves developing statistical models to evaluate end-to-end performance for current and counterfactual sensor suites, including in rare-event contexts or where operational data is scarce. It also develops workflows to determine required performance levels, inform perception hardware and software architecture decisions, estimate event exposure, and improve the rigor and efficiency of risk reporting from verification and validation outcomes. The engineer will expand methodologies to support new operational design domains and emerging challenges, collaborate with software, evaluation, test engineering, and systems safety teams, and communicate quantitative findings and recommendations to stakeholders, including senior leadership. The role also works across Product, Simulation, and Data Science teams to advance safety.
Requirements
- Bachelor’s degree or higher in computer science, mathematics, physics, engineering, or a related field.
- 10+ years of engineering experience, with demonstrated delivery of high-stakes technical roadmaps that resolved architectural friction and deployed business-critical systems.
- Experience using AI productivity tools for analysis and workflow development.
- Experience in vehicular robotics development or evaluation.
- Software development proficiency in Python or C++.
- Experience with statistical or predictive modeling.
- Experience in experimental design and developing metrics for quantitative methods.
- Deep technical knowledge in at least two of the following: state-of-the-art machine-learning techniques used in modern perception systems and large end-to-end models; quantitative risk estimation using simulators, preferably with sensors-in-loop; systems engineering fundamentals such as requirements definition and formal verification and validation methods.
- Track record of 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 and ability to manage by influence.
Nice To Haves
- Master’s degree with thesis or PhD in machine learning, statistics, robotics, or a related quantitative field.
- Autonomous driving industry experience.
- Experience testing on large-scale infrastructure and deploying production-level safety-critical systems.
- Track record of developing model-driven metrics that influence software or hardware design decisions at scale.
Responsibilities
- Define quantitative safety risk analysis approaches for 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 situations with scarce operational data to assess behavioral safety risk across a variety of contexts.
- Develop workflows to analyze required performance levels for sensing and perception tasks.
- Develop workflows to support trade studies and architectural decisions for perception hardware or software.
- Develop workflows to estimate exposure to events relevant to perception-driven behavioral risk.
- Improve quantitative rigor, standardization, execution efficiency, and reporting of end-to-end risk from verification and validation test outcomes in complex contexts.
- Expand methodologies that support entry into new operational design domains and address emerging challenges.
- Collaborate with Onboard Software and Evaluation to map perception and planner evaluation to end-to-end risk in large models.
- Collaborate with Test Engineering to cross-calibrate risk from verification and validation results across methodologies and coverage competencies, and provide actionable data to improve test tooling across public-road and closed-course tests and simulations.
- Collaborate with Systems Safety on appropriate allocation of quantitative risk across functional insufficiencies.
- Communicate complex quantitative findings and recommendations to diverse stakeholders, including senior leadership.
- Collaborate across Systems Engineering and with Product, Simulation, and Data Science teams.
Benefits
- Eligibility to participate in Waymo’s discretionary annual bonus program, subject to eligibility requirements.
- Eligibility to participate in Waymo’s equity incentive plan, subject to eligibility requirements.
- Generous company benefits program, subject to eligibility requirements.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
