Uber's Marketplace Signals team needs to build and optimize foundational marketplace signals to power user experiences and drive marketplace efficiency.
Requirements
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
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.
Responsibilities
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.
Other
B.S. in Statistics, Mathematics, Computer Science, or Machine Learning
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
