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Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. Zoox’s System Design and Mission Assurance (SDMA) team is responsible for constructing the safety case for each milestone. We play a foundational role for the success of the company. As a safety research engineer focused on quantitative risk assessment, you will help Zoox to improve and expand our existing safety risk assessment framework. The safety risk assessment framework is a critical part of the overall safety case and informs the decision-making in every aspect of the technology.
In this role, you will:
Lead efforts to improve the fidelity of Zoox’s safety and progress performance metrics
Apply distributed computing algorithms to efficiently analyze petabytes of urban driving and vehicle testing data
Develop and standardize best practices of safety risk assessment across the company
Develop and automate the tooling of the the risk assessment framework
Contribute to the improvement and evolution of the Safety Case of Zoox technology, in close collaboration with cross-functional teams including Software, Hardware, Vehicle Development, Fleet Operations, Safety Strategy and Operations, Legal, etc.
Qualifications
M.S. or higher degree in an Engineering or Science discipline with a strong focus on Statistics, Probability Theory, or Data Science
Proficiency in quantitative analysis/modeling tools
Proficient with SQL / Spark / Python for interfacing with Zoox’s urban driving and simulation data
At least 3 years of relevant work experience in understanding and quantifying safety risks
Collaborative team player with strong written and in-person communication skills
Bonus Qualifications
Ph.D. in an Engineering or Science discipline with a strong Data Science or Statistics focus
Publications in the field of quantitative risk assessment for safety engineering
Experience with human behavior data
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