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. We’re looking for a Senior Growth Optimization Engineer to design and build the intelligence layer that drives rider growth — the systems that decide who gets what, when, and why. You’ll be hands on building the backend systems that automate targeting, experimentation, and optimization across the rider funnel. Your work will enable the company to make data-driven decisions at scale — optimizing incentives and comms to continuously improve rider acquisition, activation and retention. This is a highly cross-functional role at the intersection of backend engineering, data science, and product experimentation. You’ll ensure that growth decisions are measurable, repeatable, and continuously improving over time. You will: Design and implement backend services and data pipelines that power targeting, experimentation, and incentive optimization. Work with data science to productionize models into various growth surfaces (e.g., churn prediction, message timing optimization, LTV scoring). Build automation frameworks to determine which users to message, through what channel (push, email, in-app), and at what cadence — ensuring we don’t spam or over-message users. Integrate with experimentation and analytics platforms to make growth initiatives measurable, testable, and repeatable. Develop feedback loops and metrics systems that monitor conversion, spend efficiency, and campaign ROI. You have: 5 years of backend or data-platform engineering experience. Strong programming skills in C++, Java, or Python. Solid grasp of data architecture concepts — ETL, streaming pipelines, data quality, and feature stores. Strong SQL and analytics proficiency — comfortable exploring datasets, defining metrics, and validating hypotheses. Proven experience working closely with Data Science teams to productionize models or decision systems (e.g., recommendation, targeting, budget optimization). We prefer: Experience in the ride-hailing, delivery, or marketplace domain, especially around incentives, dynamic pricing, or growth automation. Exposure to campaign orchestration systems (Braze, OneSignal, Firebase, custom pipelines) and multi-channel communication logic. Familiarity with causal inference, LTV modeling, or offline experimentation analysis. Background integrating data science workflows into production environments with CI/CD and model lifecycle management. #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 $204,000 — $259,000 USD
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