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 Waymo Mapping team's goal is to build a high resolution map of the world to support safe autonomous driving. We work on creating the map using a combination of automatic and manual techniques and build the infrastructure to store, process, and distribute the map. Our team collaborates with several other Waymo teams that consume map data. In this hybrid role, you will report to an Engineering Manager In this role, you will: Design, train, and deploy machine learning models to automate the creation of Waymo's HD maps, unlocking scale for the Waymo Driver. Apply and advance state-of-the-art ML techniques, including Vision-Language Models (VLMs) and other Generative AI approaches, to pioneer new solutions in mapping automation. Own the complete model development lifecycle, from data mining and processing to model training, evaluation, validation, and productionization. Collaborate closely with partner ML teams, such as Waymo Perception and Waymo AI Foundations, to adapt cutting-edge research into scalable, reliable, and production-grade solutions. You have: 8+ years of hands-on experience in Machine Learning, with a strong focus on computer vision and/or deep learning. Proficiency in at least one major deep learning framework (e.g., TensorFlow, PyTorch, JAX). Demonstrated experience owning problems end-to-end and working across various parts of the systems stack to deliver results. B.S. in Computer Science, a similar technical field, or equivalent practical experience. It's a Bonus if you have: M.S. or Ph.D. degree in Computer Science or a related discipline. Familiarity with foundation models and techniques for model adaptation (e.g., few-shot learning, transfer learning, domain adaptation). A track record of publications in top-tier ML/CV conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV). Experience with C++. Direct experience with mapping or GIS is a bonus but not required. The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process. Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range $251,000 — $310,000 USD

Requirements

Must-haves

In this hybrid role, you will report to an Engineering Manager
Design, train, and deploy machine learning models to automate the creation of Waymo's HD maps, unlocking scale for the Waymo Driver.
Apply and advance state-of-the-art ML techniques, including Vision-Language Models (VLMs) and other Generative AI approaches, to pioneer new solutions in mapping automation.
Own the complete model development lifecycle, from data mining and processing to model training, evaluation, validation, and productionization.
Collaborate closely with partner ML teams, such as Waymo Perception and Waymo AI Foundations, to adapt cutting-edge research into scalable, reliable, and production-grade solutions.
8+ years of hands-on experience in Machine Learning, with a strong focus on computer vision and/or deep learning.
Proficiency in at least one major deep learning framework (e.g., TensorFlow, PyTorch, JAX).
Demonstrated experience owning problems end-to-end and working across various parts of the systems stack to deliver results.
B.S. in Computer Science, a similar technical field, or equivalent practical experience.
M.S. or Ph.D. degree in Computer Science or a related discipline.
Familiarity with foundation models and techniques for model adaptation (e.g., few-shot learning, transfer learning, domain adaptation).
A track record of publications in top-tier ML/CV conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
Experience with C++.

Nice-to-haves

Direct experience with mapping or GIS is a bonus but not required.

Application prep

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

Keywords to mirror

machine learningmlai

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Vision