2026 Summer Intern, PhD, Software Engineer, Predictive Planner ML/DL

Waymo
RemotePosted 9 March 2026

Job Description

2026 Summer Intern, PhD, Software Engineer, Predictive Planner ML/DL MOUNTAIN VIEW, CALIFORNIA, UNITED STATES INTERN SOFTWARE ENGINEERING 3948 Apply now Add to favorites View favorites 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 develops full-stack cutting edge ML solutions for autonomous vehicles behavior improvements to achieve Waymo's critical milestones and realize its ML vision. This encompasses modeling enhancements via feature engineering, data shaping, model design and tuning. This team plays a key role in translating and applying advancements from foundation models to realize real product impacts. 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: Collaborate with a world-class team of researchers and engineers to develop cutting edge large models for planning of autonomous vehicles Incorporate the large models into production planning system for real-world applications with improved performance You have: Currently pursuing a PhD degree in Computer Science, Machine Learning, Robotics or a similar discipline Experience with Deep Learning, Generative Models Python coding skills Familiar with deep learning frameworks such as PyTorch, JAX, Tensorflow We prefer: Publications on top-tier conferences such as: CVPR, ICCV, ECCV, ICLR, ICML, NeurIPS, IROS, CoRL, ACL, EMNLP, etc Experience in Autonomous Driving domain 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 We appreciate your interest in Waymo. Waymo is proud to be an equal opportunity employer, committed to creating a culture of belonging and maintaining a supportive workplace for all employees. We welcome applicants of all backgrounds, and employment decisions are based on a candidate’s qualifications, experience, and alignment with job requirements and business needs. Waymo does not discriminate against, and prohibits harassment of, any applicant or employee based on race, color, sex, sexual orientation, gender identity, religion, national origin, age, disability, military status, family status, pregnancy, genetic information or any other basis protected by applicable law. Waymo will also consider for employment qualified applicants with criminal records in accordance with applicable law. Waymo is committed to making sure our hiring process is accessible for all candidates. If you need assistance applying for a role or participating in the interview process due to a disability, please let the recruiting team know or email waymo-candidatesupport@google.com. (This email address is intended to be used only for requesting accommodations as part of the appl ... (truncated, view full listing at source)
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