2027 Summer Intern, PhD, Data Science

Location: Mountain View, CA, USA; San Francisco, CA, USA Department: Pipeline (N/A)

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 Data Science team works on a wide variety of evaluation and modeling problems, including safety evaluation, the simulation technology, driving quality and rider experience. This role works with a variety of teams across the company to inject data science rigor and perspective, and to influence development direction in many of the critical systems in self-driving technology and fleet operations.

As a Data Science intern, you may join one of these Data Science Subteams:

World Model Eval

Safety Eval Tech

Data Science Safety

Driving Quality Data Science

Simulation Data Science

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

Analyze large-scale on-road and simulation data to build metrics, statistical models, and predictive features that quantify the Waymo Driver's safety and driving quality performance

Develop and validate statistical / ML methodology — estimation, uncertainty quantification, sampling, and extrapolation — to use or evaluate large-scale foundation models and draw reliable conclusions about rare and critical events from limited data

Build tools and pipelines that turn one-off analyses into repeatable workflows, partnering with engineering teams to automate data exploration, triage, and reporting

You have

Pursuing PhD in a quantitative field (e.g. Statistics, Computer Science, Mathematics, Physics, Engineering, Computational Social Science)

Proficiency in programming with Python (or R), including data manipulation, wrangling, and visualization

Strong statistical theory foundation

We prefer

Experience in machine learning applications and complex data analysis, or familiarity with SQL and/or C/C++

Experience in processing and interpreting high dimensional data such as images/videos

Demonstrated research capabilities through publications and a strong understanding of statistical methodologies and foundation models

Prior internship experience (Autonomous Driving and generative AI preferred)

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.

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