Safety Research Engineer - Quantitative Risk Assessment at Zoox
Zoox · Foster City, United States Of America
- Office in Foster City
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:
- Develop and implement methodologies and data pipelines to evaluate the efficacy of human operators and the robustness of off-robot software and hardware systems. Establish a framework for incorporating field and service data into predictive metrics.
- Collaborate cross-functionally with engineering teams to analyze component-level validation results and their impact on overall system performance.
- Drive continuous improvements to achieve performance requirements for human operators and cloud software.
- 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 2 years of relevant work experience in understanding and quantifying safety risks or other types of risk
- Collaborative team player with excellent 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
- Experience with human behavior data
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. 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.
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.
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.
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