Senior/Staff Systems Engineer, Nuro

• 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/L4 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

Desirable

• The Systems Engineering team is responsible for the requirements, architecture, and validation of autonomous driving capabilities across engineering disciplines
• This includes designing performance metrics, evaluation methods, and criteria for success, which the team then drives cross-functional via requirement definition and system validation
• Systems Engineering works at the intersection of hardware, software, and robot operations, with a deep understanding of technologies in all three
• We are a small, high-impact team that sets the checkpoints for autonomy deployment
• As a Senior/Staff Systems Engineer working on Autonomy Verification, you are responsible for verifying that the behavior of the Nuro Driver is safe to deploy in our target ODD
• 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, metric implementation, and test strategy development
• Create requirements for the behavior of an autonomous system, ensuring safe operation within its ODD and compliance with the rules of the road
• Develop generalizable behavior models and metrics to verify that the autonomous system satisfies these requirements. Leverage a combination of existing metrics in safety literature and ML-driven models for this
• Propose and leverage diverse test strategies - synthetic and log simulation, onroad logs, closed course testing, third-party accident reconstructions - to verify requirements
• 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
• Collaborate closely with Behavior, Perception, Data Science, Product, Legal and Public Trust teams while developing acceptance criteria for metrics and tests
• Partner with simulation infrastructure and test integration teams to set up automated verification workflows