Research Intern: LLM Reasoning for Autonomous Driving - Honda Research Institute USA

Research Intern: LLM Reasoning for Autonomous Driving

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Research Intern: LLM Reasoning for Autonomous Driving

Job Number: P26INT-04
Honda Research Institute USA (HRI-US) is seeking a self-motivated research intern to work on LLM-guided reasoning and behavior adaptation for autonomous driving. This individual will develop methods to incorporate LLM-based reasoning into learning-based planning approaches, with the goal of improving the scalability and robustness of these approaches in complex, interactive autonomous driving scenarios.
Mountain View, CA

 

Key Responsibilities

 

  • Develop a low-latency LLM reasoning module for understanding driving scenarios and determining appropriate behavioral adaptations.
  • Integrate LLM reasoning with learning-based planning methods.
  • Develop and train generative planning models for complex autonomous driving scenarios.
  • Design methods for conditioning, guiding, or adapting generative planners based on scene context and LLM-generated behavioral decisions.
  • Evaluate the proposed methods in closed-loop simulation, including challenging interactive and long-tail driving scenarios.

 

Minimum Qualifications

 

  • Research experience in one or more of the following areas: motion prediction, motion planning, machine learning, autonomous driving, or robotics.
  • Strong programming skills in Python and/or C++.
  • Familiarity with modern deep learning frameworks such as PyTorch.

 

Bonus Qualifications​

  • Ph.D. candidate in robotics, computer science, electrical engineering, or a related field.
  • Publication record in motion planning, prediction, autonomous driving, machine learning or robotic systems (e.g., ICML, NeurIPS, CoRL, RSS, CVPR, ICRA, IROS).
  • Experience with motion transformer models, diffusion models, LLM-based reasoning, MetaDrive, nuPlan, etc.

 

Years of Work Experience Required   0
Desired Start Date  May 2027
Internship Duration  3 Months
Position Keywords  

​LLM Reasoning, Generative Planners, Autonomous Driving, Simulations

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