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.
With over 1M RO miles per week, it is critical that Waymo is able to understand and assess the behavior of all its vehicles- both in the field and in simulation- with automated algorithms. In this role, you will collaborate across teams to bring state-of-the-art ML to production systems that accomplish this, building out what is effectively Waymo's reward model. This is a pivotal component to Waymo's ability to scale and reach its goals.
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:
- Debug an ML model's performance, understand why it is performing well in some areas but not in others
- Add new features to a model, including modifying a data pipeline and the model architecture
You have:
- Experience with at least 1 deep learning framework (Jax, Pytorch, Tensorflow, etc)
- Strong Python programming
- Experience training and debugging ML models in a research or industry context
We prefer:
- C++ Programming skills
- Experience training RL agents, including
- Experience with REINFORCE, PPO, or other RL algorithms
- Learned rewards or other techniques beyond manual reward tuning
- Experience applying ML to robotics applications
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.
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