Staff Systems Engineer, Simulation Systems Verification and Validation Lead

Description

The company is building a fully autonomous vehicle fleet and a supporting service for urban mobility, with the goal of running it on public roads.

Simulation lets the team test driving software across far more scenarios than real road driving allows. To count toward the safety case, simulation results must show how closely the simulator matches reality and how much uncertainty the remaining gap adds to safety metrics.

This is a technical leadership role owning simulation verification and validation across the full autonomy stack. The work sits on the critical path to scaling the service safely and is highly visible to leadership.

You will work with simulation, perception, planning, hardware, safety, data science, and systems engineering teams.

The role suits someone who thinks in systems, can lead a complex multi-team program, and knows how to validate a model of a closed-loop system that includes an AI controller.

Responsibilities

• Own the simulation verification and validation strategy across integration levels, from sensors alone up to full system behavior, to build the safety case for fully autonomous driving on public roads.
• Define the datasets, metrics, and methods used to compare simulated and real results.
• Run a recurring cross-functional simulation validation program with the simulation, perception, planning, systems engineering, safety, and data infrastructure teams. Set milestones and cadence, track risks and dependencies, and push decisions to closure.
• Work with statisticians and data scientists to build 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.
• Coach engineers across teams on verification and validation practice and systems thinking.

Requirements

• A master's degree or higher in systems, aerospace, mechanical, electrical, or robotics engineering, computer science, physics, mathematics, or a related field.
• 8+ years of verification and validation work on safety-critical systems with software or autonomy, such as autonomous vehicles, ADAS, aerospace guidance or flight software, or robotics.
• A track record of leading technical programs across several teams, taking a vague problem to a delivered result.
• Hands-on experience validating a simulation or model against real-world data so its results could support a decision. Experience with a closed-loop system that has software or a learned controller is preferred.
• Strong systems thinking: you can split a system into integration levels, define interfaces and the evidence each level needs, and link component 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. Experience modeling uncertainty and failure rates also counts.
• You have a choice of optional items below.
• Optional: experience with sensor simulation (camera, lidar, radar), neural rendering or generative scene synthesis, or perception evaluation metrics.
• Optional: experience evaluating motion planning or behavior in closed-loop simulation at scale.
• Optional: 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.
• Optional: hands-on Python and SQL.
• Optional: a Ph.D. in a relevant field.

Conditions

Equal opportunity applies to all candidates.