Machine Learning Research Scientist, Nuro
Prediction & Smart Agents
Eligible for an annual performance bonus + equity
3 days a week in office (Mountain View, CA)
Autonomous delivery vehicle manufacturer
Be an early applicant
Autonomous delivery vehicle manufacturer
501-1000 employees
Be an early applicant
Eligible for an annual performance bonus + equity
3 days a week in office (Mountain View, CA)
501-1000 employees
Company mission
To better everyday life through robotics.
Role
Who you are
- Education: You have an M.Sc. or Ph.D. (preferable) focusing on one or more of the following areas: Computer Science, Artificial Intelligence, Mathematics, or a closely related field
- Expertise: Subject matter expertise and research experience in one or more of the following: sequential decision-making, prediction, Imitation Learning, Deep Reinforcement Learning, generative modeling, large models (pretraining/finetuning), or machine learning for robotics
- Technical Skills: You have strong problem solving and programming skills in Python (required) and C++ (beneficial) and ML frameworks such as PyTorch
- Collaboration: Strong culture fit and good team player
- Experience: You have 2+ years of deploying machine learning systems onboard, ideally in the area of prediction
- Publications: Demonstrated research publications in top conferences (e.g. NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, ICRA, IROS etc.)
What the job involves
- As a key member of the Prediction and Smart Agents team, you will focus on building state-of-the-art models for predicting the behavior of surrounding traffic
- These models are crucial for our autonomous system, as they will be deployed onboard as part of our planning stack and used offboard for realistic closed-loop simulation
- You will explore novel machine learning methods to solve challenging real-world problems in autonomous driving
- This work includes using generative sequence modeling approaches for robustly predicting complex, interactive traffic situations
- It requires deep reasoning about the intentions of other road users and how their behaviors influence safe and correct driving decisions
- You will also use different input modalities, including End-to-End (E2E) approaches, for predicting other agents
- A vital component of this role is building smart, controllable agents to enable effective closed-loop training in simulation
- If you are passionate about solving challenging new problems, leading impactful research, and seeing your work deployed onto real robots, we encourage you to apply!
- Design and build scalable, machine learning-based prediction systems to generate multi-modal, realistic, and kinematically feasible trajectories
- Conduct cutting-edge research in generative sequence modeling and sequential decision-making. Areas of interest include, but are not limited to:
- Scalable generative sequence modeling approaches
- Marginal, conditional, and joint distribution modeling for interactive agents
- Transformer-based encoder-decoder architectures
- Large generative models and diffusion models
- Controllability of agents via conditioning, guidance, and other techniques
- Collaborate closely with the Planning team to design realistic and controllable agents for closed-loop simulation, enabling agent training via Reinforcement Learning (RL)
- Mitigate accumulated uncertainties across interconnected autonomy components
- Collaborate across various autonomy teams to develop holistic solutions for top challenges, proposing ideas, prioritizing
- Derive practical, deployable solutions and see them deployed on real-world vehicles
Our take
Nuro offers custom-built autonomous vehicles for the delivery of physical goods, rather than people. Its vehicles have a distinctive, futuristic, design that has not only made the vehicles noticeable from a marketing point of view, but, has also made its vehicles stand out to other road users, improving safety.
Nuro is an exciting addition to the autonomous vehicle landscape. Without a passenger inside the vehicle, it has been able to sidestep some of the safety issues that have plagued other autonomous vehicle brands. Additionally, the company has landed several high-profile partners, including Uber, Walmart, Chipotle, and Kroger.
With home deliveries at an all-time high, many companies are looking for ways to get goods to customers’ homes as fast as possible. Low-cost, efficient services such as Nuro's offering are becoming increasingly attractive. Following Series E funding, the company is focusing on growing new commercial partnerships and scaling its technology.
Steph
Company Specialist at Welcome to the Jungle
Insights
-29% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Apr 2025
$203m
SERIES E
Nov 2021
$600m
SERIES D
Total funding: $2.3bn
Company benefits
- Free Caltrain pass and commuter benefits
- Company stock options
- Work from home opportunities
- Health insurance
Company HQ
Old Mountain View, Mountain View, CA
Leadership
Jiajun Zhu
(Co-Founder & Co-CEO)After an MA in Computer Science at the University of Virginia, Jiajun worked as Principal Software Engineer at Google for over 8 years. He left this role in August 2016 to co-found Nuro with Dave.
Dave Ferguson
(Co-Founder & Co-CEO)Experienced Robotics Engineer with stints at Google (Computer Vision and Machine Learning Lead) and Intel (Senior Research Scientist). PhD in Robotics from Carnegie Mellon University.
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