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 Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing and training the Waymo Driver. Our team is a diverse,, and collaborative group of software engineers, machine learning (ML) engineers, and data scientists. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. By applying machine learning, we model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions.
To increase the fidelity and steerability of our simulations, we employ the latest ML technologies such as large foundation models trained on our datasets and diffusion technology. We also invest in capable infrastructure that allows us to quickly set up and roll out multiple scenarios to rigorously test our autonomous driving systems.
In this hybrid role, you will report to a Senior Engineering Manager
You will:
- Be part of a world-class applied ML team dedicated to advancing ultra-realistic autonomous vehicle (AV) simulations by leveraging Generative AI technologies.
- Apply deep domain expertise in ML, especially GenAI, to push the boundaries of simulation realism and autonomous driving capabilities.
- Independently manage the entire lifecycle of product innovations, from prototyping to productization, scaling simulations and data processing systems.
- Work within a collaborative applied ML engineering team that transforms research ideas into production-ready solutions.
You have:
- 7+ years experience in applied Deep Learning
- 7+ years coding and design skills
- 7+ years of experience solving complex production problems using state-of-the-art ML techniques
- 7+ years of experience taking research to production
- Expertise in Data Analysis or Data Science
We prefer:
- PhD degree in Computer Science or a similar discipline
- Direct experience in Generative AI, including multi-modal foundation models and Diffusion models.
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.
What We Do
Waymo is an autonomous driving technology company with a mission to make it safe and easy for people and things to move around. With the Waymo Driver, we can improve the world’s mobility while saving thousands of lives. Waymo reaches out to candidates from official channels only (e.g. directly from @waymo.com email addresses, or through our recruiters or sourcers who are noted as such on LinkedIn). We do not contact candidates about career opportunities through instant messaging apps like Telegram, email addresses from domains other than waymo.com (such as Gmail addresses), direct messages on Twitter, Facebook, and Instagram, or text messages. Visit waymo.com to check out our official job listings.
