Waymo
2027 Summer Intern, PhD, Research, RSI for Autonomous Driving
Mountain View, CA, USA. Posted 21 days ago
The role
You will conduct literature research on SOTA in RSI, physics AI foundational models, autonomous driving foundational models, and World Action models. You will design new data and post-training recipes, code and implement the RSI system, and inspect training results.
What you will do
- Literature research of SOTA in RSI, physics AI foundational models, autonomous driving foundational models, World Action models and connect the SOTA to their research projects to improve driver qualit
- Design new data and post-training recipe to RL the driver with the critic model and world model in a close loop setup
- Coding and implementing the RSI system
- Inspect training results and ablation studies to iterate the algorithm design
Required qualifications
- Currently pursuing a PhD in Computer Science, Robotics, Machine Learning, or a related quantitative field
- Depth in foundational AI model post-training, especially RL
- Fluency in using AI coding agents
- Fluency in one of the RL training framework such as Rex, Verl, NeMo-RL
- Fluency in AI model training basics such as transformer architecture, hyperparameter tuning, overfitting debug
- Familiarity with autonomous driving, physics AI, VLA, or world models
Nice to have
- Depth in RL for robotics or autonomous driving models
- Depth in world action models or video generation models
- Experience in Recursive Self-Improvement training for AI models
Benefits
- Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements
Before you apply
- 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
About the company
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases.