2027 Summer Intern, PhD, Research, Behavior Post-training

Waymo•San Francisco, CA

7d•Hybrid

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 focus areas 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. As a research intern, you will work on synthetic driving data and model post-training, partnering with industry leaders on projects that contribute to the company. This is a hybrid onsite internship. Resumes are accepted on a rolling basis until the role is filled; candidates interested in multiple roles must apply to each individually. The expected hourly rate is $85. Interns may participate in the company’s benefits programs, subject to eligibility requirements.

Requirements

Currently pursuing a PhD in Computer Science, Machine Learning, Robotics, Electrical Engineering, or a related technical field.
Familiarity with methods of sampling from large models.
Experience with post-training methods such as SFT, RL, and preferences.
Experience with modern deep learning frameworks such as PyTorch and JAX.

Nice To Haves

Experience working with open- and closed-loop decision-making models in robotics.
Experience with synthetic data generation and evaluation.
Prior projects using LLM-as-a-judge.

Responsibilities

Build tools for sampling, selecting, and discarding synthetic driving data, using testable hypotheses about how the data will improve models.
Train and evaluate models using mixtures of synthetic and logged data.
Present and write about methods for synthetic data generation and training.