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Senior/Staff Safety Research Engineer - Quantitative Risk Assessment

Leads quantitative risk assessment for autonomous vehicle safety, improving metrics, analyzing petabytes of driving data with distributed computing, and automating safety frameworks. Requires MS/PhD in engineering/science with statistics focus and 3+ years experience.

162k – 291kFoster City, CAOtherHybrid

About the role

Responsibilities

  • 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 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

Skills

SQLSparkPythonStatisticsProbability TheoryData ScienceDistributed Computing

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