About the job
As a Senior/Staff Systems Engineer working on Autonomy Verification, you are responsible for verifying that the Nuro Driver is safe to deploy in our target ODD and complies with the rules of the road. This requires prior experience with the development or validation of autonomous systems, and a collaborative nature to work closely with a variety of teams across Nuro: Autonomy Software, Simulation, Product, and Operations. You will have end-to-end ownership from requirements definition, metrics design, and test strategy development.
Responsibilities
Create requirements for an autonomous system, ensuring safe operation within its ODD and compliance with the rules of the road.
Design generalizable metrics and acceptance criteria to verify that the autonomous system satisfies these requirements, leveraging safety standards and methodologies.
Propose and leverage diverse test strategies - synthetic and log simulation, on-road logs, closed-course testing, third-party accident reconstructions - to verify requirements.
Collaborate closely with Behavior, Perception, Data Science, Product, Legal, and Public Trust teams to develop acceptance criteria for metrics and tests.
Partner with simulation infrastructure and test integration teams to set up automated verification workflows.
Quantify coverage of the tests for our ODD, ensuring simulation realism and relevance for deployment. Link the results from the tests as evidence to support the Autonomy Safety Case.
Qualifications
Minimum
5+ years of technical work experience in a relevant area with 3+ years of experience with development or validation of autonomous vehicles/robotic systems. Experience creating behavior requirements for SAE L2, L3, or L4 autonomous systems or other robotic systems to operate safely within its ODD. Experience with simulation and real-world testing of autonomous systems. Strong understanding of the autonomy architecture - how sensing, localization, perception, prediction, behavior, and control modules interact. Hands-on software experience, with the ability to code in Python or C++. Highly collaborative in nature, with strong abilities to think and communicate analytically and effectively.
Preferred
Background in autonomous vehicles ideally with L4 AV deployment. Prior experience building computational models for driving behavior or ML based metrics for behavior evaluation. Familiarity with safety standards and methodologies like STPA, ISO-21448, ISO 8800. Experience developing a safety case or compiling evidence supporting a safety case in a structured manner.