Hiring.Camp

2027 Summer Intern, PhD, Safety Research, Human Behavior Analytics

Waymo

Location
Mountain View, CA, USA · Mountain View (US-MTV-EMF680)
Workplace
Hybrid, Onsite
Type
Internship
Department
Education
Seniority
Internship
Education
PhD

Description

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

 

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.

At Waymo, we don’t just accept differences - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know.

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
$85$85 USD

Skills

Machine LearningData Science

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