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The Media Platform team builds Uber's unified, scalable infrastructure for ingesting, processing, storing, and delivering media that powers global Safety and Trust products. As a Staff Software Engineer, you will lead the design and evolution of high-performance distributed systems that process large-scale video and media workloads reliably and cost-efficiently. Your work will directly enable real-time safety use cases by ensuring media intelligence systems — including ML-powered insights — operate with low latency, high availability, and strong compliance guarantees.
Job Responsibility
Architect and scale distributed backend systems that support media ingestion, processing, intelligence, and delivery across global regions
Improve performance, reliability, and cost efficiency of high-throughput media pipelines
Design infrastructure that enables efficient integration and execution of ML inference workloads within media systems
Drive technical strategy and long-term architectural decisions across the Media Platform
Mentor engineers and raise the bar for engineering excellence, operational rigor, and system design
Requirements
10+ years of backend engineering experience, with deep expertise in distributed systems and large-scale service architecture
Strong backend engineering experience (Go, Java, C++, or similar) with expertise in system design, performance optimization, and reliability
Experience building high-throughput, low-latency services handling large data volumes (streaming, storage, or media systems)
Nice to have
Experience building or operating media, video, or real-time streaming pipelines
Familiarity with ML-powered systems (e.g., integrating model inference services, optimizing ML workloads, or supporting ML pipelines in production)
Deep understanding of distributed systems fundamentals
Experience designing privacy-aware or compliance-driven systems at scale