Senior Safety Research Engineer, Human Factors Modeling

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)