What you'd actually do

Develop and scale state-of-the-art generative models—especially diffusion architectures, flow-matching techniques, and energy-based models —for autonomous plan generation.

Build generative models with foundation models. Leverage large language models and world foundation models for reasoning, decision making and multi-modality generation.

Optimize generative models using reinforcement learning to improve interactive reasoning. Explore reward modeling/learned verifier using generative models. Explore joint prediction and planning and self-play. Leverage generative models for active learning and world modeling.

Develop controllable generative models to guide the generation process towards desired goals, conditions and rewards.

Collaborate across autonomy teams while developing holistic solutions to top autonomy challenges. Understand issues, propose ideas, prioritize work and develop solutions to solve them, evaluate your solution by deploying the models on to the NuroDriver.

Skills

Required

Python
C++
Generative models
Diffusion models
Flow matching
Energy-based models
Autonomous driving
Robotics

Nice to have

LLMs
World foundation models
Reinforcement learning
Reward modeling
Vision-language-action models
Video generation
Text-to-image generation
Diffusion models for LLMs
Self-play
Active learning
World modeling

**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 **

In this role, you will collaborate closely with researchers and engineers on the Learned Behavior teams to tackle plan generation challenges in autonomous driving. You’ll apply state-of-the-art generative modeling techniques—ranging from cutting-edge diffusion, flow matching, energy-based models, and SoTA algorithms—in order to develop novel solutions that generate safe, comfortable, and efficient driving behaviors in the most challenging real world situations. Beyond core research, you’ll own the end-to-end lifecycle of your models, productizing them for robust, real-world autonomous driving deployments on a global scale.

**About the Work **

Develop and scale state-of-the-art generative models—especially diffusion architectures, flow-matching techniques, and energy-based models —for autonomous plan generation.
Build generative models with foundation models. Leverage large language models and world foundation models for reasoning, decision making and multi-modality generation.
Optimize generative models using reinforcement learning to improve interactive reasoning. Explore reward modeling/learned verifier using generative models. Explore joint prediction and planning and self-play. Leverage generative models for active learning and world modeling.
Develop controllable generative models to guide the generation process towards desired goals, conditions and rewards.
Collaborate across autonomy teams while developing holistic solutions to top autonomy challenges. Understand issues, propose ideas, prioritize work and develop solutions to solve them, evaluate your solution by deploying the models on to the NuroDriver.

**About You **

You have deep expertise and prior experience in some or many of the following areas:

You have a Ph.D. (preferable) or M.Sc. with 3+ years of experience working with generative models in the lab, in industry, or both.
Research experiences in generative models, particularly diffusion models, flow matching and energy-based models, for robotics, including manipulation, path planning, and autonomous driving. Experiences in vision-language-action models, reinforcement learning for generative model optimization, video generation, text-to-image generation, diffusion models for LLMs, world foundation models, and other applications of generative modeling are a bonus!
You have strong problem solving and programming skills in Python and/or C++
Strong culture fit and good team player.

Demonstrated research publications in top conferences (e.g. NeurIPS, ICLR, ICML, CVPR, RSS, CoRL etc.)

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 and $352,290/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.