Quick overview
Job description
- Design and document the scenario and test sets that establish on-road behavior performance, from minimum to comprehensive.
- Own what enters the release pipeline: define and run the scenario validity checks, and approve or refuse test sets before they are used to judge a release.
- Maintain continuous quality feedback of the artifacts test sets depend on — scenarios, taggers, graders and the taxonomy behind them.
- Turn behavior requirements into testable criteria, working with Behavior Requirements on targets and acceptance criteria that someone will sign.
- Investigate behavior deficiencies: find further instances, establish what exposure we have to them, and return them to the pipeline as test escapes.
- Distinguish genuine behavior failures from simulation artifacts, and raise simulation fidelity gaps with the corresponding teams.
Work across the organization — motion planning, simulation, evaluation, operations, safety methodology and platform — and hold the interfaces between them. - Align verification phases and cadence with the organization: what runs on a daily release, and what a significant step in exposure requires.
- Bachelor’s degree or Master’s degree in a relevant engineering or related field (e.g., Software Engineering, Electrical Engineering, Computer Science, Robotics, Advanced Controls, Aerospace, etc.).
- Experience verifying safety-critical systems, ideallyin autonomous vehicles.
- Demonstrated experience designing test cases from requirements, and assessing what a test set covers and what it misses.
- Applied statistics: sample size, confidence, and what a result does and does not support.
- Proficiency in Python and the ability to navigate a large codebase.
- Familiarity with autonomous vehicle requirements, behaviors and design methodologies.
- Strong ability to structure, document and prioritize a large number of test sets and test strategies.
- Ability to work cross-functionally in a diplomatic way, across teams that do not always agree.
- A drive for commitment and accountability, for yourself and for others.
- Trucking or heavy-vehicle exposure.
- Machine learning experience, particularly model evaluation and false-positive / false-negative trade-offs.
- Exposure to regulatory frameworks: NHTSA, ISO 26262, SOTIF.
- Familiarity with the tooling required to extract coverage and exposure from large driving-log sets.
- Comfortable working in a newly formed team, where the process has to be built rather than followed.
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve!
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