Software Engineer, Deep Learning

Waymo is an autonomous driving technology company with the mission to be the 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 One, a fully autonomous ride-hailing service, and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over one million rider-only trips, enabled by its experience autonomously driving tens of millions of miles on public roads and tens of billions in simulation across 13+ U.S. states.

Waymo is looking for ML engineers with the experience and passion to solve the autonomous vehicle driving problem with ML. We have had incredible success applying state-of-the art techniques to the driving problem in the last several years (e.g. publications (e.g. publications Wayformers, SceneTransformers). Now, we are ready to increase ML's usage to the next level. We are looking for experts in scaling ML model usage, with experience with LLMs, Vision LMs, NLP, parameter efficient fine-tuning and performance optimization, working with TPUs on Alphabet's ML stack.

In this hybrid role, you will report to a Staff Member on our Behavior team.

You will:

• Design and implement next-gen generative models to improve autonomous driving

• Follow and promote literature in the generative modeling and autonomous vehicle space

• Develop novel ways to inspect, understand, filter, improve and synthesize data

• Collaborate with a team of researchers and engineers to apply advanced generative models to production simulators or onboard use cases

You have:

• PhD degree in Computer Science, Machine Learning, Robotics or a similar discipline, or an equivalent amount of deep learning experience

• Experience with Deep Learning and Generative Models

• Coding skills, specifically Python/C++

We prefer:

• 3+ years of deep learning experience

• 5+ Publications on top-tier conferences such as: CVPR/ICCV/ECCV/ICLR/ICML/NeurIPS/IROS/CoRL/ACL/EMNLP, etc.

• Experience in generative models for domains such as images, videos, 3D, human animation, traffic, simulation using techniques such as diffusion or autoregressive models

#LI-Hybrid

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

$192,000-$243,000 USD

We appreciate your interest in Waymo. Waymo is an equal employment opportunity employer, committed to maintaining a supportive and inclusive workplace for all employees. Waymo does not discriminate against, and prohibits harassment of, any applicant or employee based on race, color, sex, sexual orientation, gender identity, religion, national origin, age, disability, military status, genetic information or any other basis protected by applicable law. Waymo will also consider for employment qualified applicants with criminal records in accordance with applicable law. Waymo is committed to ensuring equal opportunity for qualified individuals with disabilities. If you are an individual with a disability and require an accommodation to participate in the application or interview process, please let the recruiting team know or email waymo-candidatesupport@google.com. (This email address is intended to be used only for requesting accommodations as part of the application process. Other inquiries will not receive a response.)