Machine Learning intern, Behavior Planning

Nuro • Mountain View, CA

72d • $11,500 - $14,000

About The Position

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. In this role, you will be a key member of the behavior team focused on solving the hardest autonomy problems using advanced machine learning techniques. Here you will explore novel and advanced machine learning methods to solve practical real-world challenging problems in autonomous driving. This work may include using imitation and reinforcement learning to reason about high level decisions and generate executable motion plans; develop robust models to handle challenging interactive situations; reason about the intentions of other road users and how their behaviors influence safe and correct driving decisions; build end-to-end driving systems; work with complex real world datasets; and more. If you love solving challenging new problems by leading research and seeing it through to deployment onto real robots come join us! Internship candidates that are able to join for >=6 months are strongly preferred.

Requirements

• Currently pursuing a B.S. or M.S. in Computer Science, Robotics, Mathematics, or a related engineering field.
• Excellent programming proficiency in Python and a strong understanding of object-oriented programming. Solid grasp of fundamental computer science concepts, including data structures, algorithms, and software design. Experience with C++ is a plus.
• Strong foundational knowledge of machine learning concepts (e.g., supervised/unsupervised learning, model evaluation). Hands-on experience with at least one major deep learning framework (PyTorch, TensorFlow, or JAX).
• Coursework or project experience in one or more of the following is highly desirable: Deep Learning, Computer Vision, Robotics, or Reinforcement Learning.
• Demonstrated knowledge in ML systems and infrastructure, with experience in training optimization, compiler acceleration, quantization, and efficient deployment of high-performance models is a strong plus.
• Demonstrated ability to build projects, shown through coursework, personal projects (e.g., on GitHub), or a previous internship.
• A collaborative, curious, and proactive mindset paired with strong technical communication skills. Eager to learn and contribute as a team player.

Nice To Haves

• Currently pursuing a Ph.D. in Computer Science, Artificial Intelligence, Robotics, or a closely related field.
• A clear research focus in one or more of the following areas: generative and/or diffusion modeling, sequential decision making, Imitation Learning, Deep Reinforcement Learning, large models (pre-training/fine-tuning), or machine learning for robotics.
• A deep understanding of the theoretical underpinnings of modern machine learning.
• Strong programming skills in Python for rapid prototyping and experimentation with complex ML models. Experience with C++ is a plus.
• A track record of research, with publications in top-tier conferences (e.g., NeurIPS, ICLR, ICML, CVPR, RSS, CoRL).
• Intellectual curiosity, attention to detail, persistence, and the ability to work both independently and collaboratively within a research-oriented team paired with strong technical communication skills.

Responsibilities

• Work on scalable machine learning based planning and prediction systems to generate safe and feasible trajectories for autonomous driving.
• Collaborate closely within the learned behavior team to analyze autonomy system performance, understand data quality and feature representations, and modify machine learning models to develop holistic solutions to top autonomy challenges.
• Implement and train machine learning models using established frameworks like PyTorch. Test and deploy your work on real-world vehicles.
• Conduct experiments, analyze results, and present findings to the team.

Benefits

• The reasonably expected monthly pay is between $11,500 and $14,000. Your actual base pay will depend on several factors, including your experience, qualifications, education, location, and skills.

What This Job Offers

• Career Level: Intern
• Industry: Publishing Industries
• Education Level: Bachelor's degree
• Number of Employees: 501-1,000 employees