Use modern data analysis tools to turn vehicle dynamics data into actionable insights that influence engineering decisions and improve performance of autonomous vehicles.
Conduct virtual ride and handling assessments to identify critical trade-offs and lead testing activities
Analyze simulation and vehicle data to provide quick-turnaround insights on vehicle behavior, identify performance gaps, and propose hardware or software solutions.
Distill complex vehicle dynamics phenomena into clear, data-backed options for the broader engineering team to consider during design and tuning cycles.
Contribute to the core Zoox vehicle model to improve realism and simulation capabilities
Use simulation and data analysis to evaluate vehicle stability in limit-handling maneuvers and safety-critical failure modes.
5+ years of experience and a Bachelor's in Mechanical Engineering, Aerospace Engineering, or a related field
Strong first-principles command of vehicle dynamics (e.g. tire modeling, load transfer, kinematics, and frequency response).
Experience with vehicle dynamics CAE development tools, such as Dymola, IPG CarMaker, MSC Adams
Proven ability to look at complex, multi-dimensional data and extract clear actionable insight
Programming experience with Python or a similar scripting language
Ability to translate highly technical data into concise summaries and actionable recommendations for cross-functional partners.
Master’s or PhD in Mechanical Engineering with a focus on dynamics or controls.
Hands-on physical testing experience (proving grounds, Formula SAE, or professional motorsports).
Experience with DOE/optimization workflows
Strong programming experience: Python, C+
Zoox is building a fully autonomous vehicle fleet from the ground up, coupled with the ecosystem necessary to launch this technology into urban environments. By integrating robotics, machine learning, and innovative design, Zoox is paving the way for a new era of mobility-as-a-service.
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