LLM Safety Framework Development for Motorcycle Advanced Rider Assistance Systems (ARAS) - Honda Research Institute USA

LLM Safety Framework Development for Motorcycle Advanced Rider Assistance Systems (ARAS)

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LLM Safety Framework Development for Motorcycle Advanced Rider Assistance Systems (ARAS)

Job Number: P24INT-21
During the internship, you are expected to design and implement Large Language Model (LLM) frameworks tailored to enhance safety and decision-making processes in motorcycle Advanced Rider Assistance Systems (ARAS). This will involve integrating state-of-the-art LLMs and applying contextual intelligence (CI) for dynamic scenario analysis. This role offers an opportunity for applied work in natural language processing, contextual reasoning, and AI-driven safety solutions.
Mountain View, CA

 

Key Responsibilities

 
  • Conduct literature reviews and stay up-to-date with the latest advancements in Large Language Models (LLMs), contextual intelligence (CI), and safety-critical AI systems.
  • Design and implement LLM-based frameworks to enhance decision-making and safety processes in motorcycle Advanced Rider Assistance Systems (ARAS).
  • Develop software prototypes and algorithms for real-time contextual analysis and safety assessments, leveraging AI frameworks like TensorFlow, or PyTorch.
  • Test and validate the models using simulation environments such as CARLA and Unreal Engine, ensuring scalability and reliability in dynamic, real-world scenarios.
  •  Submit a paper to a top-tier AI, robotics, or vehicular technology conference or journal.

 

Minimum Qualifications

 
  • M.S. candidate in robotics, computer science, electrical engineering, or a related field.
  • Research experience in natural language processing (NLP), contextual intelligence (CI), or robotics safety systems.
  • Excellent programming skills in Python; experience with C++ is a plus.
  • Familiarity with Large Language Models (LLMs) and frameworks such as PyTorch, or TensorFlow.
  • Knowledge of motion planning, simulation tools (e.g., CARLA, Unreal Engine), or vehicular systems is highly desirable.

 

Bonus Qualifications

  • Ph.D. candidate in robotics, computer science, electrical engineering, or a related field.
  • Publication record in areas such as NLP, contextual intelligence (CI), or safety frameworks for robotic or vehicular systems.
  • Hands-on experience with simulation environments like CARLA for testing and validation.
  • Experience integrating LLMs into real-world systems, particularly for safety-critical applications.
  • Strong foundation in control theory, motion planning, or predictive modeling for autonomous systems.

 

Years of Work Experience Required  0
Desired Start Date 5/19/2025
Internship Duration 3 Months
Position Keywords Large Language Model, Natural Language Processing, Motorcycle

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