This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
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.
Job Responsibility:
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
Leverage cutting-edge ML techniques (deep learning, probabilistic modeling, reinforcement learning, etc.) to continuously refine marketplace signals
Requirements:
B.S. in Statistics, Mathematics, Computer Science, or Machine Learning
2 years of experience in software engineering with an emphasis on data-driven methodologies, deep learning, and online experimentation
Strong problem-solving skills, with expertise in ML methodologies
Experience in applying ML, statistics, or optimization techniques to solve large-scale real-world problems (e.g. ads tech, recommender systems)
Experience in ML frameworks (e.g. Tensorflow, Pytorch, or JAX) and complex data pipelines
programming languages such as Python, Spark SQL, Presto, Go, Java
Nice to have:
3+ years of experience in software engineering specializing in applied ML methods
Experience in designing and crafting scalable, reliable, maintainable and reusable ML solutions using deep-learning techniques and statistical methods
Detail-oriented, ownership and truth-seeking mindset
Values and produces analytic evidence and insight, as well as applying them to improve technical solutions
Experience working in a cross-functional and/or cross-business projects, partnering with Product, Scientists, and cross-org leads to shape the team’s strategies
Master’s degree in Computer Science, Engineering, Mathematics or related field