Uber

Build and expand highly scalable backend fare systems that power Uber’s global marketplace and critical pricing experiences. You’ll develop platform infrastructure, collaborate across teams, and help launch features impacting millions of customers.

Senior Software Engineer building the high-performance Michelangelo Feature Store and real-time feature-serving infrastructure that powers production machine learning at enterprise scale. The role combines distributed systems architecture, low-latency backend development, technical leadership, and mentorship.

Build and maintain high-quality integrations connecting Uber’s Inventory and Catalog platform with partners and merchants worldwide. This role combines software development, live integration quality ownership, and cross-functional collaboration across Catalog Engineering and operations teams.

Build production-grade agentic systems that transform complex operational workflows at Uber, embedding directly with teams to turn ambiguous problems into reliable software. This role spans backend engineering, AI-enabled workflows, production reliability, safety evaluation, and reusable platform capabilities.

Build and operate large-scale machine learning systems powering Uber’s rider personalization, ranking, candidate retrieval, and recommendation experiences. This role combines production model development, real-time feature pipelines, inference optimization, and end-to-end ML reliability.

Build the foundational iOS mapping platform behind Uber’s Rider, Driver, and Eats experiences. You’ll develop the Maps API layer and Map Display SDK used by hundreds of internal mobile engineers and millions of riders worldwide.

Senior Software Engineer building high-throughput, low-latency backend systems that power Uber’s map, location, and geospatial experiences. The role owns services end-to-end and directly supports navigation, pickup, dropoff, and real-time map interactions for millions of users.

Build the systems that help Uber optimize billions of dollars in marketplace investments by turning experiment results into trusted efficiency estimates and budget recommendations. This full-stack role spans data pipelines, Go backend services, interactive dashboards, experimentation, and production operations.