Senior/ Staff Machine Learning Research Scientist, Autonomy Generalist

Who We Are

Nuro exists to better everyday life through robotics. Founded in 2016, Nuro is a leading autonomous technology company with vehicles on road today in California and Texas.

The company’s core technology is the Nuro Driver, an integrated autonomous driving system consisting of state-of-the-art, AI-first software and custom-built sense and compute hardware.

The first commercial application of the Nuro Driver is autonomous goods delivery with our custom, electric, zero-occupant vehicles in partnership with some of the most recognized brands in the world including Uber and FedEx.

About the Role

The mandate of the learned behavior team is to use advanced machine learning techniques to accelerate software progress.

In this role, you will work closely with the software vertical teams to understand their pain points and explore novel and advanced machine learning methods to solve practical real-world challenging problems.

To name a few, using self-supervised learning to learn robust representations, exploring techniques for out-of-distribution detection to solve long tail problems, adjusting reinforcement learning techniques for motion planning, working on trajectory prediction and motion planning, investigating the robustness of models to mitigate uncertainties, or trying to build an end-to-end driving system.

If you love solving challenging new problems with a mindset of deriving practical solutions to eventually be used on the vehicle, come join us!

About the Work

• Research new machine learning problems and models
• Work on goal-based, conditional, and joint trajectory prediction and motion planning
• Investigate the consistent decision-making process
• Touch the state-of-the-art language-inspired generative modeling
• Mitigate the uncertainties accommodated through the Autonomy stack
• Build effective and efficient ML data pipelines
• Collaborate with autonomy teams to understand their pain points and priorities to define milestones of the corresponding roadmaps
• 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 an M.Sc. with 4 years of experience or Ph.D (preferable) with 2 years of experience focusing on one or more of the following areas : Computer Science, Artificial Intelligence, Mathematics, or a closely related field
• You have subject matter expertise and research in one or more of the following areas : Machine Learning, Deep Learning, Robotics (preferable)
• You have an expertise in at least two of the following domains :
• Sequential / autoregressive decision-making in interactive scenarios
• Transformers (and NLP / LLM as an example)
• Uncertainty Estimation or Robustness Improvement
• You have strong problem solving and programming skills in C++ or Python
• Strong culture fit and good team player
• Demonstrated research publications in any of the major conferences (RSS, ICRA, CoRL, CVPR, ICLR, ICML, NeurIPS, ICCV, AAAI, etc.)

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.

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $202,350 and $303,050 / 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.