2027 Summer Intern, PhD, Research, World Action Model

The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!

You will:

• Research, implement, and evaluate world action models for end-to-end autonomous driving
• Collaborate with research and engineering teams to improve the Waymo World Model
• Conduct cutting-edge research and potentially communicate research findings to the wider academic community via technical reports and/or publication

You have:

• Currently pursuing a Ph.D. in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field
• Strong publication record in top-tier AI/ML or robotics conferences
• Hands-on experience training and evaluating deep learning models for autonomous driving or robotics applications
• Strong Python coding skills with expertise in modern deep learning frameworks (e.g., PyTorch, JAX, TensorFlow)
• Deep understanding of modern neural network architectures and learning paradigms

We prefer:

• Experience with diffusion / flow matching models
• Experience with world action models in autonomous driving or robotics applications
• Familiarity with autonomous driving datasets
• Experience with open-source foundation models

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.