Join Waymo as a Summer Intern in Safety Research focusing on Human Behavior Analytics. Engage in cutting-edge research at the intersection of AI and cognitive science while contributing to impactful projects.
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. The Human Behavior Analytics (HBA) team, part of the Waymo Safety team, conducts research and development on computational road user behavior models and other methods and tools used for evaluating the behavior and safety of the Waymo Driver. This work typically exists at the intersection between AI/ML and cognitive science and is done in close collaboration with other Waymo teams, in particular SW Research, Systems Engineering, Simulation and Data Science. The HBA team also engages extensively in research with external academic partners. 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:
- Survey the state-of-the-art in digital neuroscience / cognitive science and mechanistic interpretability
- Develop models able to represent some select aspects of human driving behavior not typically accounted for by existing data-driven ML models (e.g., collision avoidance, road user interaction or visual behavior)
- Explore and demonstrate different ways in which the internal mechanisms of these models can be interpreted and explained
You have:
- A strong research background and expertise in cognitive science and / or neuroscience
- Expertise in contemporary AI and machine learning
- Strong documented computational skills (math and coding)
We prefer:
- Specific experience from research on mechanistic interpretability
General Perks:
- Help solve challenging problems with a direct impact on the company
- Competitive compensation packages with a housing/relocation bonus (if applicable)
- Medical, dental, and vision insurance
- Fun intern events and networking opportunities
Onsite Perks:
- Free breakfast, lunch, dinner, and snacks
- Free access to Google shuttles
- Onsite gym