Senior Software Systems Engineer - Simulation Verification & Validation

Zoox•San Diego, CA

48d

About The Position

Simulation is central to ensuring the safety and scalability of autonomous vehicles at Zoox. In this role, you will help ensure our next-generation, GenAI-powered simulator is accurate, trustworthy, and effective at evaluating autonomous driving software in a rich virtual world, with dynamic agents and realistic sensor data. You’ll collaborate with autonomy, safety, and simulation teams to assess how well the simulator predicts real-world on-road performance, then drive improvements through a mix of exploratory data analysis, metrics and validation design, and coding robust pipelines at scale. Your work will directly support Zoox’s ability to safely scale autonomous driving across increasingly complex environments.

Requirements

6+ years of experience in autonomous robotics, sensor processing (lidar, camera, radar), or analyzing complex systems.
Proficiency in Python and data analysis (e.g., Pandas, NumPy, SQL), with a solid foundation in data visualization and basic statistical methods (e.g., histograms, probability distributions, simple hypothesis testing).
Strong critical and analytical thinking, including interpreting complex data to identify impactful insights or root causes.
Strong written and verbal communication skills, with the ability to produce clear engineering design documents and collaborate effectively across teams.
BS, MS, or Ph.D. in Computer Science, Mechanical Engineering, Robotics, or related field.

Nice To Haves

Experience with one or more components of Autonomous Vehicle software stack (e.g., Perception, Prediction, Planning) or simulated testing modalities (closed-loop, open-loop, etc.)
Experience with systems engineering, system requirements, or testing of complex systems.
Experience applying statistical methods to system validation (e.g., confidence intervals, p-values, power analysis)

Responsibilities

Design and implement metrics to measure and reliably monitor the accuracy and fidelity of simulated sensors, agents, and virtual environments.
Develop simulator validation strategies, including data mining and dataset selection.
Conduct data-driven analyses at both granular and large scale to identify root causes of simulation inaccuracies by comparing simulation outputs to real-world data, and translate those insights into production-quality validation pipelines.
Write design proposals and drive execution while proactively communicating risks to partner teams.
Build alignment and consensus on simulation validation criteria with Autonomy, Safety, and Simulation teams.