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Zoox aims to ensure the safety and scalability of autonomous vehicles by developing an accurate, trustworthy, and effective GenAI-powered simulator to evaluate autonomous driving software in realistic virtual environments.

Requirements

• 5+ 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

• BS, MS, or Ph.D. in Computer Science, Mechanical Engineering, Robotics, or related field.
• Strong written and verbal communication skills, with the ability to produce clear engineering design documents and collaborate effectively across teams.