2026 Summer Intern, PhD, Perception at WAYMO LLC

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

29 May, 26

Salary

85.0

Posted On

28 Feb, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, JAX, PyTorch, Tensorflow, Machine Learning, Computer Vision, 3D Object Detection, Tracking, Open Vocabulary Detection, 3D Occupancy Detection, Semantic Segmentation, Foundation Models, Self-Supervised Learning, Forecasting, Audio Perception

Industry

technology;Information and Internet

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. Machine Learning models are at the core of Waymo's fully autonomous driving technology. Our models allow 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 perception, planning and control while collaborating with hardware and systems engineers. If you're curious and passionate about Level 4 autonomous driving, we'd like to meet you. Waymo interns work with leaders in the industry on projects that deliver significant impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skillset. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship! This internship will be based on-site at our headquarters in Mountain View, CA. You will: Design and implement state-of-the-art multi-modality (camera/radar/lidar/audio) and multi-task perception models. Potential project areas include: 3D object detection and tracking, Open vocabulary detection applying world knowledge models, 3D occupancy detection, Semantic segmentation, Large-scale foundation models, Pre-training and self-supervised learning through forecasting. Train and evaluate ML models on our vast and high fidelity data from Waymo driving logs. Gain experience using large scale ML infrastructure and working in a team environment. You have: Enrolled in a PhD program in Computer Science, Robotics, or a similar technical field of study or enrolled in a master's program with a strong publication record. Experience in Python Experience building ML models with JAX, PyTorch or Tensorflow We prefer: Strong track record of high quality ML / CV research. Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV, PAMI. Experience in object detection, segmentation, multiple-object tracking audio perception or occupancy detection. 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

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Responsibilities

Interns will design and implement state-of-the-art multi-modality perception models focusing on areas like 3D object detection, tracking, and large-scale foundation models. They will also train and evaluate ML models using vast, high-fidelity data from driving logs while gaining experience with large-scale ML infrastructure.