2027 Summer Intern, PhD, Research, VLM Harnesses for AV Planning
About The Position
Waymo’s AI Foundations team develops machine-learning solutions for open problems in autonomous driving, with the goal of safely operating Waymo vehicles in many cities and under all driving conditions. The team’s areas of focus include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation, and it fosters collaborations with other research teams in Alphabet. In this full-time, hybrid onsite summer internship, you will develop and evaluate harnesses that enable vision-language models (VLMs) to plan for autonomous vehicles. You will design scenario preprocessing and postprocessing systems, test them in closed-loop driving simulation, and communicate research motivations and findings. The role may also involve sharing research with the academic community through technical reports or publications. Interns work on impactful projects alongside industry leaders and have opportunities to apply and expand their skills.
Requirements
- Currently enrolled in a PhD program in computer science, statistics, applied mathematics, physics, or a related technical field.
- Familiarity with major machine-learning frameworks such as JAX and PyTorch.
- Experience using coding agents for auto-research.
- At least 3 years of experience with deep learning, computer vision, and generative models such as VLMs or LLMs.
Nice To Haves
- Publications at top-tier conferences such as CVPR, ICCV, ECCV, ICLR, ICML, NeurIPS, IROS, or CoRL.
- Substantial involvement in and contributions to high-impact industry AI projects.
- Experience with vision-language models, multimodal prompting or reasoning, or autonomous-driving simulation and planning.
Responsibilities
- Design and implement scenario preprocessors, including visual rendering, scene representations, and multimodal prompting, to present driving scenarios effectively 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 research motivations and findings to technical and non-technical audiences.
- Conduct cutting-edge research and potentially share findings with the wider academic community through technical reports and/or publications.
Benefits
- Eligible to participate in the company’s benefits programs, subject to eligibility requirements.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
Ph.D. or professional degree
