Staff Systems Engineer, Simulation Systems Verification and Validation Lead

Zoox•Foster City, CA

5d•$208,000 - $287,000

About The Position

Zoox is seeking a Simulation Systems Verification and Validation (Sim VnV) Lead to own simulation validation across the full autonomy stack. The role defines how simulation is validated at sensor, perception, planning, and full-pipeline levels, leads the cross-functional program that executes the work, and establishes evidence about when and where simulated miles can support safety clearance decisions. The position works closely with simulation, perception, planning, hardware, safety, data science, and systems engineering teams, and is a highly visible technical leadership role on the critical path to safely scaling Zoox’s service. The successful candidate will bring systems thinking, the ability to lead complex programs across teams, and expertise validating models of closed-loop systems that include AI controllers. Responsibilities include defining datasets, metrics, and comparison methods; partnering on estimators that combine simulated and real-world results into safety measures; documenting methods and results; and mentoring engineers in verification and validation practices.

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.
A record of leading technical programs across several teams, from an ambiguous problem statement to a delivered result.
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 the ability to break a system into integration levels, define interfaces and evidence needed at each level, and connect 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 or power priors, importance sampling, or rare-event estimation; similar experience modeling uncertainties and failure rates is also acceptable.

Nice To Haves

Experience with sensor simulation (camera, lidar, radar), neural rendering or 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 such as NASA-STD-7009, ASME V&V 10/20/40, ISO 21448 (SOTIF), UL 4600, ISO 26262, or ISO 34502.
Hands-on Python and SQL.
Ph.D. in a relevant field.

Responsibilities

Own the end-to-end simulation verification and validation strategy across integration levels, from sensors-only through full-system behavior, to support a safety case for fully autonomous driving on public roads.
Define datasets, metrics, and comparison methods.
Lead a recurring cross-functional simulation validation program with simulation, perception, planning, systems engineering, safety, and data infrastructure teams; set milestones and cadence, track risks and dependencies, and drive decisions to closure.
Partner with statisticians and data scientists on estimators that combine simulated and real-world results into safety performance measures.
Write methodology documents and validation reports, and present results, risks, and recommendations to engineering and executive leadership.
Mentor engineers across teams in verification and validation practices and systems thinking.