<div><p>Waymo is an autonomous driving technology company with the mission to be the worlds most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The Worlds 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.</p></div><p>The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include foundation models, LLM/VLM, pre-training, reinforcement learning, video generation, world models, and robust evaluation.</p> <p>You will:</p> <ul> <li>Build large-scale sensor data for training and evaluating LLM/VLM models, with a special focus on semantics understanding and reasoning.</li> <li>Enable large-scale training and eval for LLM/VLM models with high-quality, targeted sensor data.</li> <li>Create data strategies for advancing our critical businesses: large-scale sensor data collection, business-driven sensor data sampling, long-tail data mining, large-scale auto-labeling, targeted efficient human labeling, human-in-the-loop sensor data curation and quality improving.</li> <li>Define proper eval metrics for measuring the semantics understanding and reasoning capability for our LLM/VLM models.</li> <li>Set up and evolve the working structure between multiple teams across Waymo, where we maximize reuse of infrastructure and tooling.</li> <li>Responsible for defining and delivering large-scale and high-quality sensor dataset for foundation model training and evaluation. </li> </ul> <p>You have:</p> <ul> <li>Track record in building dataset for LLM/VLM training and evaluation.</li> <li>Track record in improving LLM/VLM with high-quality data and eval.</li> <li>Experience in large-scale data for training and eval. </li> <li>Experience in collaborating with horizontal teams, from model teams, infrastructure teams, and data teams, to advance key product success.</li> </ul> <p>We prefer:</p> <ul> <li>Experience in large-scale distributed systems, data, eval, or products.</li> </ul><div><div><div><p><span>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. </span></p> <p><span>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. </span></p></div><div>Salary Range</div><div><span>$281,000</span><span>—</span><span>$356,000 USD</span></div></div></div>