2026 Summer Intern, PhD, World Modeling at Waymo

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

24 Dec, 25

Salary

60.1

Posted On

25 Sep, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Computer Vision, Python, Generative Models, Deep Neural Networks, Reinforcement Learning, Bayesian Inference, Hierarchical Learning, Robust Evaluation

Industry

technology;Information and Internet

Description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. 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. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. 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. You will: Solve research problems in world modeling and reasoning in autonomous driving systems. Prototype and iterate research ideas. Present research findings to a wide audience within Waymo, with the goal of publishing results to the research community. You have: Currently enrolled in a PhD program in Computer Science, Robotics, or a similar technical field of study. Research experience in computer vision and machine learning. Strong programming skills in Python. We prefer: First-authored publications from top-tier Computer Vision, graphics, or robotics conferences. Research experience in generative models or large language models. Hands-on experience with deep neural networks and familiarity with at least one type of deep learning frameworks such as PyTorch, Jax, Tensorflow, etc. General Perks: Help solve challenging problems with a direct impact on the company Competitive compensation packages with a housing/relocation bonus (if applicable) Medical, dental, and vision insurance Fun intern events and networking opportunities Onsite Perks: Free breakfast, lunch, dinner, and snacks Free access to Google shuttles Onsite gym 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. At Waymo, we don’t just accept differences - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know. 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 $60.10—$60.10 USD

Responsibilities

Solve research problems in world modeling and reasoning in autonomous driving systems. Prototype and iterate research ideas while presenting findings to a wide audience.