Who We Are

Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale—empowering a safer, richer, and more connected future.

About the Role

As a Senior Research Engineer, Collision Avoidance Modeling on the Systems Engineering team, you will work closely with the autonomy software, operations, simulation, and data platform teams to validate autonomy performance. You will be responsible for assessing conflict scenarios by architecting and developing tooling which quantifies collision risk. You will be responsible for identifying through analysis and testing any collision-related risks resulting from functional insufficiency. You will ensure that these risks are managed and tested appropriately, driving software architecture and development, engineering roadmaps, validation, on-road operations, and the safety case.

About the Work

• Design, develop, and maintain methods and software which evaluates collision risk in the context of conflict scenarios in on-road logs or in simulation by modeling both crash dynamics and predictive behavior of agents.
• Develop labeling processes and simulation software for the extraction of parameters from logged conflict scenarios.
• Leverage scientific literature and real-world data from public roads and closed course/track to model evasive maneuver responses and collision severity.
• Evaluate, track, and report collision risk, making strategic recommendations based on the results for test realism improvements, changes to autonomy architecture, and mitigations.
• Communicate effectively in a cross-functional product development team and present risks and requirements effectively.

About You

• 5+ years of technical work experience in a relevant area, of which 3+ years should be in robotics software research and development (offboard or onboard).
• Experience with both simulation and on-road testing of autonomous vehicles using well-defined metrics to score good driving behavior, with strong algorithmic problem solving skills and Python experience.
• Highly collaborative in nature with strong abilities to think and communicate analytically and effectively, both verbal and written.
• Self-starter and fast learner - you should be passionate about picking up new skills and approaching unstructured problems from first principles while prioritizing and managing workload to meet critical project deadlines.

Nice to have

• Experience with naturalistic driving data involving collisions and collision avoidance.
• Familiarity with STPA, ISO 21448, and ISO 8800.
• Experience working with real-world datasets (e.g. NuScenes) and simulators (e.g. Carla).

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $176,400 and $264,600 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. #LI-DNP