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2027 Summer Intern, Machine Learning, MS/PhD, Simulation Realism (World Model)

Waymo

Mountain View, California, United States

ML Engineering

Posted 25 minutes ago

internonsite

Verified open on Nov 6, 2026 · posted today

Job 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.

Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you. 

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:

  • Implement, train, and evaluate generative models (such as diffusion models, flow matching, or autoregressive transformers) for video and physical world simulation.
  • Experiment with unified 3D/4D and spatiotemporal representations that generalize across diverse scenes, vehicle platforms, and sensor modalities.
  • Investigate conditioning, fine-tuning, or distillation methods to improve temporal consistency, physical realism, and inference speed for closed-loop simulation.
  • Partner with mentors and researchers across Waymo and frontier AI labs at Google to adapt foundation world models and translate research prototypes into Waymo’s simulation pipeline.

 

You have:

  • Currently pursuing an MS or PhD in Computer Science, Machine Learning, Computer Vision, Robotics, or a related field.
  • Solid background in deep learning and computer vision, with hands-on experience in modern generative modeling (e.g., diffusion models, flow matching, VAEs, or transformers).
  • Strong coding skills in Python and practical experience training and debugging models in PyTorch or JAX.

 

We prefer:

  • Prior research or projects in video generation, world models, or generalized 3D/4D scene representations.
  • Exposure to 3D computer vision, multi-view geometry, physical/geometric priors, or multimodal sensor data (Camera, LiDAR, Radar).
  • Contributions to open-source projects or publications in ML, vision, or robotics venues (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML).

 

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 USDThe 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
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This role is classified as ML Engineering.

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