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Research Intern: Vision-Language-Action and World Models for Autonomous Systems
Job Number: P25INT-43
Honda Research Institute USA (HRI-US) is seeking a highly motivated intern to join its intelligent autonomy and AI research efforts. This role focuses on advancing approaches for handling rare, long-tail scenarios in autonomous driving by exploring complementary modeling paradigms. The candidate will work with modern multimodal and predictive modeling techniques, including vision-language(-action) models and world modeling approaches, to better understand and represent complex real-world situations. The work will contribute to improving the robustness, interpretability, and reliability of intelligent autonomous systems.
San Jose, CA
Key Responsibilities
- Develop multimodal and predictive models, including vision-language(-action) and world models, using post-training (e.g. fine-tuning) to improve performance in rare, safety-critical scenarios.
- Curate and preprocess datasets from public benchmarks with a focus on long-tail and edge-case conditions.
- Design experiments to evaluate model behavior in complex scenarios and analyze results to identify strengths, limitations, failure modes, and potential improvements in rare-event settings.
- Collaborate with cross-functional teams to align research direction and technical goals.
- Contribute to a portfolio of patents, academic publications, and prototypes to demonstrate research value.
Minimum Qualifications
- M.S. in Computer Science, Electrical Engineering, Robotics, Artificial Intelligence, Machine Learning, or a related field.
- Strong background in machine learning, deep learning, or multimodal AI, including experience with vision-language(-action) models and/or world models.
- Experience with model training, fine-tuning, or large-scale data processing.
- Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow).
- Strong written and verbal communication skills, with the ability to present technical ideas and results clearly to diverse audiences.
Bonus Qualifications
- Ph.D. in Computer Science, Electrical Engineering, Robotics, Artificial Intelligence, Machine Learning, or a related field.
- Familiarity with autonomous systems, robotics, or mobility-related datasets.
- Experience with parameter-efficient training methods (e.g., LoRA, adapters).
- Exposure to long-tail/edge-case analysis or safety-critical systems.
- Strong analytical and problem-solving skills for diagnosing model behavior.
- Publication record in top-tier conferences (e.g., CVPR, ICCV, ECCV, WACV, NeurIPS, ICLR).
Years of Work Experience Required
0
Desired Start Date
8/31/2026
Internship Duration
3 Months
Position Keywords
Mutimodal learning, vision-language(-action) models, world models, long-tail scenarios, autonomous driving
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