Simulation is central to ensuring the safety and scalability of autonomous vehicles at Zoox. The role aims to ensure the accuracy, trustworthiness, and effectiveness of Zoox's GenAI-powered simulator in evaluating autonomous driving software in a rich virtual world with dynamic agents and realistic sensor data.
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.
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.
Other
- 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.
