**About the Role** The Delivery Pricing & Incentives team plays a pivotal role in shaping Uber’s Delivery business—including food delivery, groceries, and more. We build innovative products and scalable systems that keep the marketplace efficient, reliable, and ready for continued growth. Our systems power hundreds of millions of consumers and millions of merchants around the world, and that footprint is expanding rapidly. We’re looking for engineers who are passionate about building high-impact, consumer-facing products and solving complex engineering challenges. In this role, you'll work across the full end-to-end flow of Uber's Delivery products—from building machine learning models and offline data pipelines, to developing real-time services, online model serving, and shaping user experiences. You’ll have the opportunity to tackle challenging problems at scale and drive impactful outcomes across consumer journey. **What You Will Do** - Design and build innovative products used by hundreds of millions of consumers, in collaboration with talented engineers, Product Managers, Product Operations, and Applied/Data Scientists. - Develop reliable, scalable, and high-performance software solutions. - Write clean, maintainable, and high-quality code. - Champion best practices for testing, monitoring, and overall system health to ensure long-term reliability. - Analyze and decompose complex software systems, partnering with cross-functional teams to ensure scalability, testability, and maintainability. - Lead alignment across the team on solutions to ambiguous problems, thoughtfully evaluating technical trade-offs. **Basic Qualifications** - Minimum 2 years of experience in software engineering - Experienced programming in Java, Golang, C++, Python or related language - Strong track record of contributing to and delivering impactful product features, balancing quality with timely execution. **Preferred Qualifications** - Strong experience in Software Design and Architecture, Data Engineering, or Modeling, having experience in scalable distributed systems. - Good problem-solving and analytical skills. Knowledge of algorithms, data structures, and complexity analysis. - Communicate effectively and collaborate well across teams to deliver impactful results. - Think strategically and work to align technical decisions with broader business goals, always considering impact. - Machine learning hands on experience is preferred, however deep ML knowledge is not required For San Francisco, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$167,000 per year - USD$185,500 per year. For all US locations, 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.