Staff Optimization Engineer, Dynamic Pricing

Uber is seeking a Staff Optimization Engineer to join their Dynamic Pricing team, focusing on maintaining marketplace reliability through real-time supply/demand balancing. This role is crucial in Uber's mission to make transport accessible, generating billions in annual bookings through network efficiency optimization. The position involves building scalable real-time systems for market state analysis, demand forecasting, and ML-based predictions. The ideal candidate will have a PhD in a relevant field and extensive experience in optimization modeling and algorithm development. Working in a hybrid environment from San Francisco, you'll collaborate with a diverse team of engineers, researchers, and economists to shape the technical direction of pricing systems across Uber's global marketplaces. The role offers competitive compensation ranging from $223,000 to $248,000 annually, plus equity and comprehensive benefits. This is an opportunity to make a significant impact on Uber's core pricing strategy and marketplace efficiency while working with cutting-edge optimization and machine learning technologies.