Staff Systems Engineer, Simulation Systems Verification and Validation Lead (Autonomous Vehicles)

Location: Foster City, California, United States; hybrid workplace

Company

Zoox is developing a full-stack autonomous mobility solution for cities.

What you will do

• Own the end-to-end simulation verification and validation strategy from sensor-level integration through full-system behavior to support a safety case for fully autonomous driving.
• Define datasets, metrics, comparison methods, and evidence needed to assess simulator fidelity and uncertainty.
• Lead a recurring cross-functional program with simulation, perception, planning, systems engineering, safety, and data infrastructure teams; set milestones, track risks and dependencies, and drive decisions to closure.
• Partner with statisticians and data scientists on estimators combining simulated and real-world results into safety performance measures.
• Write methodology documents and validation reports, present risks and recommendations to engineering and executive leadership, and mentor engineers in V&V and systems thinking.

Requirements

• M.S. or higher in Systems, Aerospace, Mechanical, Electrical, or Robotics Engineering, Computer Science, Physics, Mathematics, or a related field.
• 8+ years of experience in verification and validation of safety-critical systems containing software or autonomy, such as autonomous vehicles, ADAS, aerospace guidance and flight software, or robotics.
• Experience leading technical programs across several teams from an ambiguous problem statement through delivery.
• Working-level experience validating a simulation or model against real-world data so its results could support a decision, preferably for a closed-loop system with software or a learned controller in the loop.
• Strong systems thinking, including decomposing systems into integration levels, defining interfaces and evidence, and connecting component-level results to system-level claims.
• Experience deriving or implementing estimators that fuse simulated and real data, such as control variates, prediction-powered inference, Bayesian hierarchical models, power priors, importance sampling, or rare-event estimation; similar experience modeling uncertainties and failure rates is acceptable.

Nice to have

• Experience with sensor simulation for camera, lidar, or radar; neural rendering; generative scene synthesis; or perception evaluation metrics.
• Experience evaluating motion planning or behavior in closed-loop simulation at scale.
• Familiarity with model credibility and safety standards including NASA-STD-7009, ASME V&V 10/20/40, ISO 21448, UL 4600, ISO 26262, or ISO 34502.
• Hands-on Python and SQL experience.
• Ph.D. in a relevant field.

Culture & Benefits

• Hybrid work arrangement in Foster City, California.
• Highly visible technical leadership role on the critical path to safely scaling an autonomous mobility service.
• Cross-functional collaboration across simulation, perception, planning, hardware, safety, data science, and systems engineering.
• Mentorship opportunities across engineering teams.