Research Intern - World-Action Model / VLA for Autonomous Driving

Job Description:

Job Description

As a Research Intern for World-Action Models / VLA for Autonomous Driving, you contribute to research projects at the forefront of the ADAS/AD industry. You will work at the intersection of VLAs, generative modeling and world models, and contribute to research that pushes toward scalable autonomy. Key responsibilities include:
* Designing and training world-action models (autoregressive / diffusion-based) that predict future sensor observations or latent states conditioned on ego actions.
* Integrating world models with planning for end-to-end or model-based driving policies.
* Summarize research findings in high-quality paper and/or patent submissions.
You will collaborate closely with other researchers, and strong work is expected to lead to top-venue publications and/or product impact

Candidate Requirements:

Qualifications

Basic Qualifications
* Ph.D. student in Computer Science, Robotics, Computer Engineering, or a related field (must be a currently enrolled student).
* Minimum GPA of 3.0
* Hands-on experience with at least one of: generative models (diffusion, autoregressive transformers, VAEs), world models / video prediction, or end-to-end autonomous driving.
* Solid fine-tuning skills and proficiency with deep learning frameworks.
* Experience with reinforcement learning and/or model-based planning.
Preferred Qualifications
* Publication record in top venues including CVPR, ICCV, ECCV, ICLR, NeurIPS and ICML.
* Familiarity with driving benchmarks such as NavSim and Bench2Drive.
* Experience with large-scale distributed training and multi-modal / video data pipelines.
* Able to work independently, with strong research and problem-solving skills.
* Good communication and teamwork skills