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Salary: USD 149,000 - 190,000 / annual
Waabi is a Physical AI company founded by AI visionary Raquel Urtasun, leading the development of autonomous transportation technology for commercial trucks and robotaxis. The company is backed by world leaders in AI, automotive, logistics, and deep tech, with offices in Toronto, San Francisco, Dallas, and Pittsburgh.
The Behavior Verification team sits at the heart of Waabi's safety mission, answering a critical question: is the autonomous driver's on-road behavior safe and ready for release? As a Systems Engineer in this role, you will be the rigorous gatekeeper for autonomous vehicle software releases, designing and maintaining the evidence that proves safety.
Key responsibilities include:
- Design and document scenario and test sets that measure on-road behavior performance across minimum to comprehensive coverage
- Own the release pipeline: define and execute scenario validity checks, approve or reject test sets before they judge a release
- Maintain continuous quality feedback on the artifacts that test sets depend on—scenarios, taggers, graders, and the taxonomy behind them
- Convert behavior requirements into testable, measurable criteria in collaboration with the Behavior Requirements team
- Investigate behavior deficiencies: identify additional instances, quantify exposure, and feed findings back into the pipeline as test escapes
- Distinguish genuine behavior failures from simulation artifacts; escalate simulation fidelity gaps to relevant teams
- Work cross-functionally across motion planning, simulation, evaluation, operations, safety methodology, and platform teams
- Align verification phases and cadence with organizational needs—determining what runs on daily releases versus what requires significant exposure steps
This is a high-impact role where your work directly influences whether autonomy software is promoted to production. You will need strong technical depth, cross-functional diplomacy, and an unwavering commitment to safety and accountability.
Qualifications:
- Bachelor's degree or Master's degree in a relevant engineering or related field (Software Engineering, Electrical Engineering, Computer Science, Robotics, Advanced Controls, Aerospace, etc.)
- Experience verifying safety-critical systems, ideally in autonomous vehicles
- Demonstrated experience designing test cases from requirements and assessing test coverage gaps
- Applied statistics knowledge: sample size, confidence intervals, and interpreting what results do and do not support
- Proficiency in Python and ability to navigate large codebases
- Familiarity with autonomous vehicle requirements, behaviors, and design methodologies
- Strong ability to structure, document, and prioritize large numbers of test sets and test strategies
- Ability to work cross-functionally in a diplomatic manner across teams with differing perspectives
- Drive for commitment and accountability, both personal and organizational
Bonus/nice-to-have:
- 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 tooling to extract coverage and exposure from large driving-log datasets
- Comfort working in newly formed teams where processes must be built rather than followed
