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Waymo

2027 Summer Intern, MS/PhD, Software/ML Engineer, Simulation

Posted One Month Ago
Be an Early Applicant
In-Office
Mountain View, CA, USA
70-70 Annually
Internship
In-Office
Mountain View, CA, USA
70-70 Annually
Internship
Build multimodal data pipelines combining vehicle sensor and 3D map data for machine learning. Prototype Vision-Language Model workflows, create evaluation datasets, measure precision and recall, improve detection accuracy, and integrate automated labeling into storage and simulation workflows.
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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.

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:

  • Design and build multimodal data pipelines in Python or C++ that combine vehicle sensor data (camera, LiDAR) and 3D map data for machine learning models
  • Prototype and iterate on Vision-Language Model (VLM) workflows to automatically detect and categorize complex real-world driving scenarios and road changes
  • Build ground-truth evaluation datasets, measure model precision and recall, and systematically improve detection accuracy
  • Integrate automated labeling pipelines into data storage and simulation testing workflows

You have:

  • Currently pursuing a MS or PhD in a quantitative or technical field (such as Computer Science, Robotics, Machine Learning, or a related area)
  • Strong programming skills in Python or C++
  • Experience with data analysis, SQL, and basic statistics

We prefer:

  • Experience with computer vision, Vision-Language Models (VLMs), or prompt engineering
  • Familiarity with 3D geometry, coordinate transforms, or sensor data processing
  • Experience working with large-scale datasets or distributed data pipelines

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.
Hourly PhD Pay
$85—$85 USD
HQ

Waymo Mountain View, California, USA Office

1600 Amphitheatre Pkwy, Mountain View, CA, United States, 94043

Waymo San Francisco, California, USA Office

San Francisco, United States

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