Machine Learning Research Scientist: Generative Models for Behavior Modeling

1 week ago

Mountain View, United States Nuro Full time
Who We Are

Nuro exists to better everyday life through robotics. Founded in 2016, Nuro has spent eight years developing autonomous driving (AD) technology and commercializing AD applications. The Nuro Driver™ is our world-class autonomous driving system that combines AD hardware with our generalized AI-first self-driving software. Built to learn and improve through data, the Nuro Driver™ is one of the few driverless autonomous technologies on public roads today.

Nuro has raised over $2B in capital from Fidelity, Bailie Gifford, T. Rowe Price, Google, and other leading investors. We've partnered with some of the world's most respected brands including Uber, FedEx, Domino's, Walmart, Kroger, and 7-Eleven.

About the role

In this role, you will be a key member of the behavior team focused on solving the hardest autonomy problems. Here you will explore novel and advanced machine learning methods to solve practical real-world challenging problems in autonomous driving. You will be focusing on researching and developing state of the art generative models, with an emphasis on diffusion models, and bring advancements in this field to the AV domain.

About the Work
  • Work on scalable generative models, with a focus on diffusion models for behavior models.
  • Learn a distribution of future behaviors of our autonomous vehicle and other onroad agents (e.g. pedestrians, vehicles, cyclists). Apply the model to various tasks such as planning, prediction, data generation, simulation, and so on.
  • Research SoTA algorithms to improve generative models' performance and optimize their latency. This includes alignment with reward/cost models, controllability, model scaling up and distillation, mode recovery, fine-tuning with closed-loop RL, etc.
  • Research experiences we are looking for are generative models and diffusion models for autonomous driving and robotics. However, experiences in video generation, text-to-image generation, image in-painting/out-painting, etc. are also welcome.
  • Collaborate across autonomy teams while developing holistic solutions to top autonomy challenges. Understand issues, propose ideas, prioritize work and develop solutions to solve them.
  • Derive practical solutions and deploy them on the NuroBot.
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 experience on generative models.
  • You have subject matter expertise and research in one or more of the following areas: scalable generative and diffusion models, generative model alignment with reward/cost models, controllability, distillation, mode recovery, fine-tuning with closed-loop RL, applications to autonomous driving and robotics, and other experiences such as video generation, text-to-image generation, in-painting/out-painting and so on.
  • 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, ICRA)

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $138,225 and $207,575 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.

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