San Francisco, California, USA
3 days ago
Sr. Staff Engineer, Paid Marketing Engineering
Uber is spending a significant amount of marketing budget on advertising each year, to attract and engage our customers - Riders, Drivers, Couriers, and Eaters. We do this across channels ranging from TV ads and posters to digital advertising through mobile and web channels. The AdTech team is building the technology capabilities to scale this advertising capability, using data to drive intelligent optimization and automation of the process. We work from the beginning of the loop: starting with budgeting and spend allocation across the world using models to the granular optimization of what content to show to whom and when. The team is currently building systems to manage and partially automate marketing spending. We leverage outstanding machine learning techniques to drive sign-ups and maximize the efficiency of billion-dollar advertising budgets. This area is ripe for disruption with the advent of GenAI. Join the team if you are interested in building Uber's next-gen Marketing optimization engine that fully leverages the latest in AI. **What you will do:** - Set the architectural vision: Define and drive the technical direction for the Paid Marketing Technical Stack, partnering closely with Engineering, Product, Applied Science, Marketing Stakeholders - Lead major platform initiatives: Own and scale systems across the Paid Marketing Technical Stack and lead critical cross-functional initiatives. - Mentor and inspire: Provide technical leadership and coaching to a high-performing team of engineers, helping foster an innovative and collaborative culture. - Build for scale and reliability: Design, develop, and deploy systems that are resilient, extensible, and easily integrated across multiple Uber apps, Lines of business and advertising partners / channels. - Collaborate across Uber: Work with cross-functional and cross-company teams to ensure that the Marketing Stack works effectively to drive business growth. - Keep a HIgh Bar On Engineering Excellence: Keep the bar high on sustainable engineering by following best engineering practices, producing best in class of code, documentation, testing and monitoring. **Basic Qualifications:** - 10+ years of experience in developing and deploying machine learning models and algorithms in production environments - Experience with large-scale distributed data processing pipelines. - Strong programming skills in languages such as Java or GoLang. **Preferred Qualifications:** - Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field - Demonstrated ability to work with cross-functional partners to drive business outcomes through a platform approach - Domain expertise in Advertising / Marketing with preference for building Buy-Side Marketing Technologies. - Excellent communication skills and the ability to collaborate effectively with cross-functional teams For San Francisco, CA-based roles: The base salary range for this role is USD$257,000 per year - USD$285,500 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link [https://www.uber.com/careers/benefits](https://www.uber.com/careers/benefits). Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together. Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A). Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
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