Primary record

Senior Software Engineer, Collision Avoidance Testing

Nuro Indexed employerMountain View, California (HQ) · Nuro HQ - Mountain View, CA
Source-hosted applyChecked 5h agoFull-Time
Apply at Nuro

Nuro receives this application through Greenhouse. Babu Careers does not claim delivery.

Workplace

On-site

Employment

Full-Time

Published

Aug 11, 2026

Closes

No date supplied

The role

Who We Are

Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides.

Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles.

With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected.

Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors.

About the Role

As a Senior Software Engineer, Collision Avoidance Testing, you will work closely with the onboard autonomy, evaluation infrastructure, data science, operations, and simulation teams to evaluate the performance of the autonomous vehicle in collision avoidance scenarios. You will be responsible for identifying gaps in onroad and simulation tests, designing appropriate tests to fill those gaps, reviewing test outcomes, and iterating on test design. You will analyse the results, recommend product changes, and report on residual risk both to leadership and in the safety case.

About the Work

• Using human benchmarks from naturalistic data, develop statistical models that drive strategic decisions as a function of test volume, system performance, and confidence level.

• Identify and design realistic scenarios

Requirements

Department: Systems