Job description

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 We’re a team applying ML to push autonomy performance forward. As a Perception ML Engineer, you’ll develop and improve perception models, with ownership of modeling, training, and evaluation. Your work will directly impact how autonomous systems understand rare scenarios, adapt to global geographies, and scale safely. Design and advance perception models that: Improve scene understanding from real sensor data, including 3D and spatial representations Generalize across sensor platforms, geographies, and rare driving scenarios Meet requirements for model quality and onboard inference runtime Tailor Your Impact: Applied ML Depth: Own model architecture, loss design, training, and experiments that deliver measurable perception improvements. Collaborative Delivery: Partner with ML Data Infrastructure and autonomy engineers, contributing across the stack when needed while keeping primary ownership in modeling. About the work You’ll solve autonomy’s hardest perception challenges through applied ML and rigorous experimentation: Develop and improve perception models, making choices about architecture, representations, objectives, and training. Design controlled experiments and ablations to understand model behavior and validate improvements. Diagnose model failures and distinguish limitations in modeling, supervision, training data, and optimization. Collaborate with autonomy and infrastructure engineers to turn sensor data and failure analysis into targeted model improvements. About You BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area. 4+ years of industry software engineering experience with Python fluency and C/C++ familiarity. Proven ability to lead cross-functional technical projects from design to completion. You have hands-on depth in developing, training, debugging, and improving ML models. You bring perception experience, or an exceptionally strong growth trajectory with evidence of quickly building depth and delivering substantive ML results in new domains. Bonus Points Experience with occupancy, 3D scene understanding, or onboard perception models. Familiarity working with synthetic or autonomous driving data. At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $193,930.00 and $291,150.00/year 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

Requirements

Must-haves

Improve scene understanding from real sensor data, including 3D and spatial representations
Generalize across sensor platforms, geographies, and rare driving scenarios
Meet requirements for model quality and onboard inference runtime
Applied ML Depth: Own model architecture, loss design, training, and experiments that deliver measurable perception improvements.
Collaborative Delivery: Partner with ML Data Infrastructure and autonomy engineers, contributing across the stack when needed while keeping primary ownership in modeling.
BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area.
4+ years of industry software engineering experience with Python fluency and C/C++ familiarity. Proven ability to lead cross-functional technical projects from design to completion.
You have hands-on depth in developing, training, debugging, and improving ML models.
You bring perception experience, or an exceptionally strong growth trajectory with evidence of quickly building depth and delivering substantive ML results in new domains.

Nice-to-haves

Experience with occupancy, 3D scene understanding, or onboard perception models.
Familiarity working with synthetic or autonomous driving data.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpython

Platform: greenhouse
Effort: quick

Benefits

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