- Location
- Mountain View, CA, USA; San Francisco, CA, USA · Mountain View (US-MTV-EMF680) · San Francisco (US-SFO-MKT555)
- Type
- Internship
- Department
- IT
- 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 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.