2026 Summer Intern, MS/PhD, Software Engineer, Predictive Planner Research

Mountain View, CA USAFull-TimeInternSoftware Engineering

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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.
Our team's mission is to scale the production Waymo Driver using cutting edge ML techniques. In this team, you will be working on state-of-the-art ML models for autonomous driving and have the opportunity to improve Waymo's onboard performance in the real world.
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!

Design and implement experiments for post-training of large behavior models
Evaluate and iterate on the model within the closed-loop simulation environment to rigorously assess the model's performance and identity failure modes
Leverage modern reinforcement learning algorithms and our industry-leading datasets to enhance the model's performance
Design and implement experiments for post-training of large behavior models
Evaluate and iterate on the model within the closed-loop simulation environment to rigorously assess the model's performance and identity failure modes
Leverage modern reinforcement learning algorithms and our industry-leading datasets to enhance the model's performance

Strong hands-on SWE skills
Experience in AV planning and related research
Pursuing a PhD in a relevant field
Strong hands-on SWE skills
Experience in AV planning and related research
Pursuing a PhD in a relevant field
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.