Opportunities · Internship
Conflict Behavior Intern - MS/PhD
Waymo · Mountain View, CA
Role overview
What you'll own
- Analyze large-scale real-world and simulated driving logs to evaluate model accuracy, characterize edge cases, and optimize trade-offs
Requirements and eligibility
- Currently pursuing an Master's or PhD degree in Computer Science, Engineering, Physics, Statistics, Data Science, or a related quantitative field
- Interns are also eligible to participate in the Company’s generous benefits programs, subject to eligibility requirements.
Dates for this one
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Posted
Sep 17, 2026
Applications close
Dec 16, 2026
90 days left
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Read the full listing context
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. Waymo's Systems Engineering team works together to blend software and hardware systems in groundbreaking new ways. We set the high performance standards that ensure our vehicles run smoothly and keep passengers safe, then design and perform the tests that validate that performance.
We're looking for talented teammates who’ll help us maintain strong teamwork and are passionate about driving results. 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: • Calibrate and validate physical reachability and safety-margin metrics against expert human evaluations to quantify "proactive caution" in complex scenarios • Analyze large-scale real-world and simulated driving logs to evaluate model accuracy, characterize edge cases, and optimize trade-offs • Partner cross-functionally to integrate quantitative safety signals into automated event triage and release-readiness workflows You have: • Currently pursuing an Master's or PhD degree in Computer Science, Engineering, Physics, Statistics, Data Science, or a related quantitative field • Proficiency in Python and/or C++ • Experience analyzing, wrangling, and visualizing large-scale datasets • Demonstrated analytical and statistical skills for validating quantitative models We prefer: • Familiarity with SQL • Familiarity with autonomous vehicles, robotics, crash safety analysis, or human driving behavior modeling • Experience working with rare-event modeling, anomaly detection, or highly imbalanced datasets in complex real-world domains (e.
g., autonomous systems, robotics, experimental physics, crash safety, or healthcare) • Solid foundation in machine learning and statistical evaluation fundamentals 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 Masters Pay $70—$70 USD 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.
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