About the job
The mandate of the prediction team is to use advanced machine learning techniques to improve the behavior of the Nuro Driver. 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.
Responsibilities
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
Qualifications
Minimum
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
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.
Strong problem solving and programming skills in Python (required) and C++ (beneficial) and ML frameworks such as PyTorch.
Strong culture fit and good team player.
You have 2+ years of deploying machine learning systems onboard, ideally in the area of prediction.
Demonstrated research publications in top conferences (e.g. NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, ICRA, IROS etc.)
Preferred
Deep background in Embodied AI for robotics, Causal reasoning, Model interpretability and explainability, Joint prediction and planning, Understanding of Diffusion Models.