Sr Software Engineer, AdTech

Sr Software Engineer, AdTech Department: Engineering Team: Backend Location: Sunnyvale, United States Type: Full-Time Uber invests a substantial annual marketing budget to attract and engage customers—including Riders, Drivers, Couriers, and Eaters—across a variety of channels, from traditional TV and print ads to digital mobile and web advertising. The **AdTech team** is responsible for building the technological foundation to scale this advertising effort. We leverage data science, including models and LLMs, to achieve intelligent optimization and automation throughout the entire process. Our work spans the advertising loop, from initial budgeting and spend allocation to the granular optimization of which content is shown to whom and when. By maximizing the efficiency of a multi-billion-dollar advertising budget, the AdTech team is a critical enabler of Uber's growth, sharply focused on maximizing user acquisition and retention through effective marketing. The **Measurement and Optimization team within AdTech** is seeking talented individuals to drive automated, intelligent decision-making for Uber's marketing investment. This is a high-impact role where you will define and execute the technical roadmap to measure, test, automate, and optimize Uber's significant marketing and brand spend. This work is crucial, as it directly drives substantial cost savings and contributes to Uber's growth across users, trips, and gross bookings. Join us if you are interested in building Uber's next-generation Marketing platform. ## **What You'll Do** - **Design and Deliver:** Design, build, and deliver end-to-end marketing features that track, measure, report, execute and test and on Billions of ad spend and achieve efficient return on investment. - **Develop Services and products:** Design, develop, and operate highly scalable and reliable services and backend systems to handle channel-specific complexities. - **AI Infrastructure Modernization:** Modernize our tech stack to build a relevant contextual layer for AI-driven systems. Bridge the gap between petabyte-scale data and LLMs by develop