The mission of the Waymo Research 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. Research areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

Waymo interns work alongside leaders in the industry on projects that deliver significant impact to the company. We believe learning is a two-way street: leveraging 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:

• Implement post-training algorithms like preference learning, RLHF, supervised fine-tuning, etc
• Curate training datasets across label sources
• Run training experiments on Waymo’s planning models
• Evaluate the performance of planning models

You have:

• Currently enrolled in a PhD program in computer science, statistics, applied mathematics, physics, or a related technical field of study
• Basic software programming or scripting skills (Python, C/C++)
• Experience with machine learning, deep learning, Foundational Models and/or LLMs
• Familiar with one of the modern deep learning frameworks (e.g. Pytorch, JAX, Tensorflow)

We prefer:

• Experience with training and evaluating LLMs and/or robotics models
• Publications from top peer-reviewed conferences (eg: CoRL, CVPR, ECCV, ICCV, Neurips, ICLR)

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.

#LI-Hybrid