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. The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the self-driving car, i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet. We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware. 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 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

Requirements

Must-haves

This internship will be based on-site at our headquarters in Mountain View, CA.
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.
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
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.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlpython

Platform: greenhouse
Effort: quick