Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.
What you'll do: We're pushing the boundaries of how well our autonomous driving models generalize to new cities and environments. A key challenge is efficiently evaluating performance in diverse scenarios using simulation. You'll contribute to a project that evaluates and improves the performance of simulation agents in new environments, ensuring we effectively measure model robustness in unfamiliar settings. You will work with state of the art foundation models, large datasets, and applying the latest modeling innovations to improve our custom architectures. This high-impact project directly influences how we validate the safety and reliability of our self-driving technology.
Required
- Enrolled in a PhD program
- Machine learning expertise
- Coding experience in Python
- Jax/Tensorflow/Pytorch ML framework experience,
Preferred
Jax experience; C++; Experience working with foundational models and/or VLMs/LLMs/transformers, robotics, AV experience
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
