Staff Software Engineer - (backend) Gen AI

Uber Uber · Consumer · Sunnyvale, CA · Engineering

Staff Software Engineer role focused on architecting and scaling distributed backend systems for media ingestion, processing, intelligence, and delivery. The role involves improving performance, reliability, and cost efficiency of high-throughput media pipelines, and designing infrastructure for efficient integration and execution of ML inference workloads within these media systems. It also includes driving technical strategy and mentoring engineers.

What you'd actually do

  1. Architect and scale distributed backend systems that support media ingestion, processing, intelligence, and delivery across global regions.
  2. Improve performance, reliability, and cost efficiency of high-throughput media pipelines.
  3. Design infrastructure that enables efficient integration and execution of ML inference workloads within media systems.
  4. Drive technical strategy and long-term architectural decisions across the Media Platform.
  5. Mentor engineers and raise the bar for engineering excellence, operational rigor, and system design.

Skills

Required

  • 10+ years of backend engineering experience
  • deep expertise in distributed systems
  • large-scale service architecture
  • Strong backend engineering experience (Go, Java, C++, or similar)
  • expertise in system design
  • performance optimization
  • 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

What the JD emphasized

  • ML inference workloads
  • high-throughput media pipelines
  • low latency
  • high availability
  • strong compliance guarantees
  • privacy-aware or compliance-driven systems

Other signals

  • ML inference workloads
  • media intelligence systems
  • large-scale video and media workloads