Uber

The **Marketplace Signals** team at Uber is responsible for building and optimizing foundational marketplace signals that power user experiences and drive marketplace efficiency. Our team ensures that key signals—such as eyeball ETA, spinner time, and supply reliability indicators—are leveraged effectively across various Uber products and levers, enabling data-driven decision-making and seamless coordination across different business functions. As a Staff Machine Learning Engineer, you will design, develop, and scale advanced ML models to enhance these signals, ensuring they are accurate, reliable, and optimized for Uber's dynamic marketplace. Your work will have a direct impact on pricing, matching, driver incentives, reliability metrics, and customer experience. **What You'll Do** - Develop and optimize ML models to enhance key marketplace signals (e.g., ETA predictions, supply availability metrics, demand forecasts). - Collaborate with cross-functional teams (Pricing, Matching, Driver Incentives, etc.) to ensure marketplace signals are effectively utilized. - Improve operational efficiency by building a centralized, scalable system for marketplace signals that serves multiple use cases. - Ensure consistency and reliability across Uber's platform by maintaining high-quality marketplace signals that inform rider and driver experiences. - Reduce technical debt by streamlining signal infrastructure and minimizing redundant computations. - Leverage cutting-edge ML techniques (deep learning, probabilistic modeling, reinforcement learning, etc.) to continuously refine marketplace signals. - Work with real-time streaming data and large-scale distributed systems to ensure Uber's signals are up-to-date and responsive to market dynamics. **What You'll Need** - 6+ years of experience in machine learning, applied data science, or AI-driven optimization in large-scale systems. - Strong ML expertise, including experience with time-series forecasting, predictive modeling, and real-time inference. - Proficiency in programming languages such as Python, Java, or Scala. - Experience with big data frameworks (Spark, Flink, Ray) and real-time data processing. - Deep understanding of Uber’s marketplace dynamics or experience in a two-sided marketplace, pricing, or matching algorithms is a plus. - Strong communication and collaboration skills to work effectively with product managers, engineers, and researchers. **Why Join Us?** - Work on high-impact machine learning problems that directly improve Uber's marketplace efficiency. - Influence key business levers that optimize Uber’s pricing, matching, and rider/driver experience. - Build centralized marketplace signals that reduce redundancy and improve operational efficiency. - Join a high-caliber, innovative team tackling some of the hardest ML challenges in the industry. If you’re passionate about using ML to optimize real-world systems at a massive scale, we’d love to hear from you! For San Francisco, CA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$223,000 per year - USD$248,000 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 is proud to be an Equal Opportunity/Affirmative Action 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.