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!

In this role, you’ll:

• Work on open-ended ML research problems for realistic simulation for the autonomous vehicle’s driving environment. 
• Frame the open-ended real-world problems into well-defined ML problems; develop and apply cutting-edge ML approaches (deep learning, generative modeling, reinforcement learning, etc) to these problems; scale them to Google-sized data pipelines; and streamline them to run in real-time on the cars.
• Collaborate with other teams, including the ML infrastructure, simulation and systems engineering teams, as well as Google Brain, DeepMind and academia.
• Get an opportunity to publish findings in academic conferences and journals, and/or externally publicize the work in public-facing blog posts.

At a minimum we’d like you to have:

• Currently enrolled in a PhD program in Computer Science, Robotics, similar technical field of study
• Experience solving problems using Machine Learning with Tensorflow, JAX or equivalent tools
• Ability to collaborate within and across teams
• Ability to independently drive a reasonably-scoped, open-ended research project
• Strong experience programming in Python with robust and efficient code

It’s preferred if you have:

• Strong track record of high quality ML research, for example demonstrated by conference publications in venues such as CVPR, ICCV, ECCV, ICML, NeurIPS, ICLR, etc.
• Experience applying machine learning to sequence modeling, behavior forecasting, simulation, or robotics
• Experience with generative models (e.g., autoregressive models, diffusion models, GANs, VAEs, etc.)