You will:- Design and implement scenario preprocessors (e.g., visual rendering, scene representations, and multimodal prompting) to effectively present driving scenarios to state-of-the-art VLMs
- Develop postprocessors that translate VLM outputs into feasible, safe trajectories for closed-loop vehicle control
- Evaluate VLM driving harnesses in closed-loop autonomous driving simulation and iterate on representations based on driving metrics
- Communicate to both technical and non-technical audiences regarding research motivations and research findings
- Conduct cutting-edge research and potentially communicate research findings to the wider academic community via technical reports and/or publications
You have:- Currently enrolled in a PhD program in computer science, statistics, applied mathematics, physics, or a related technical field of study
- Familiarity with major ML Frameworks (JAX, Pytorch)
- Experience using coding agents for auto-research
- 3+ years of experience with Deep Learning, Computer Vision, and Generative Models (such as VLMs/LLMs)
We prefer:- Publications at top-tier conferences such as CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/IROS/CoRL etc.
- Substantial involvement in and contributions to high impact industry AI projects
- Experience with Vision-Language Models (VLMs), multimodal prompting/reasoning, or autonomous driving simulation and planning
Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in.
The expected hourly rate for this full-time position is listed below. Interns are also eligible to participate in the Company's generous benefits programs, subject to eligibility requirements.
Hourly PhD Pay
$85-$85 USD
