Nuro is looking to solve challenging autonomy problems using advanced machine learning techniques to make autonomy accessible to all.
Requirements
- 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.
- 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.
- Strong programming skills in Python for rapid prototyping and experimentation with complex ML models.
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 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.
- (PhDs) Research generative sequence modeling and sequential decision making.
- Research novel and advanced machine learning methods to solve practical real-world challenging problems in autonomous driving.
Other
- Internship candidates that are able to join for >=6 months are strongly preferred.
- A collaborative, curious, and proactive mindset paired with strong technical communication skills.
- Eager to learn and contribute as a team player.
- 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 track record of research, with publications in top-tier conferences (e.g., NeurIPS, ICLR, ICML, CVPR, RSS, CoRL)
