As a safety research engineer focused on human factors modeling, you will help Zoox to continuously update and evolve our understanding of safety-critical road user behavior, and contribute to the overall safety risk assessment that will inform decision-making in every aspect of the technology development. You will be part of the SDMA Safety Research team which is scoped with enhancing the foundational approaches used in the safety case. The research you do could potentially lead to methodologies which can inform critical design aspects of the Zoox robotaxi.
In this role, you will:
Lead statistical analysis of various safety-critical human road user behaviors to inform the evaluation of Zoox autonomous driving performances. This can be based on third party naturalistic driving data or academic publications.
Lead research and experimental design for utilizing in-house data to inform safety-critical human road user behavior in the context of autonomous vehicles.
Propose and standardize processes to guide and execute the development of simulation human road user kinematic and non-kinematic parameters.
Maintain and grow a knowledge base of human road user behavior across modes, including: passenger vehicle drivers, emergency vehicle drivers, bicycle riders, pedestrians, and more.
Contribute to the development and evolution of the Safety Case of Zoox technology, in close collaboration with cross-functional teams including Systems Engineers, Software and Hardware Engineering, Vehicle Engineering, Safety Strategy, Legal, etc.
Qualifications
Ph.D. degree in an Engineering or Science discipline with a strong Human Factors focus and statistics skills
Proficiency in experimental design and multivariate statistical methodologies, e.g., causal inference with observable data, classification, dimension reduction, and other quantitative analysis/modeling tools
At least 3 years of relevant experience in modeling and analyzing the behavior of human road users based on naturalistic databases
Collaborative team player with strong written and in-person communication skills
Bonus Qualifications
Have the ability to use Python to interface with Zoox internal driving and simulation data sources
At least 5 years of relevant work experience related to human factors in safety-critical systems and, naturalistic driving data analysis
Publications in the field of Human Factors related to safety, traffic safety research, and Advanced Driver-Assistance Systems (ADAS)
Compensation and Benefits
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary range for this position is $171,000 to $282,000. A sign-on bonus may be offered as part of the compensation package. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
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Accommodations
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A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.