Senior Product Manager, Av Labs

Uber Uber · Consumer · San Francisco, CA +1 · Product

Product Manager for Uber's AV Labs, focusing on developing platforms and systems to generate high-quality autonomous driving data from real-world operations. The role involves defining product requirements, driving execution, and working with engineering, science, and operations teams to accelerate AV capabilities, particularly in areas like machine learning and semantic understanding.

What you'd actually do

  1. Own product development and execution for a meaningful AV Labs domain spanning one or more of the following: hardware systems, machine learning, semantic understanding, and data & validation platforms.
  2. Work with engineering and cross-functional partners to define product requirements, goals, milestones, and launch plans.
  3. Drive execution against roadmap priorities, identify blockers early, and help teams make effective tradeoffs.
  4. Gather insights from internal users, partner teams, data, and operational feedback to shape product improvements and prioritization.
  5. Define and monitor product metrics to evaluate product performance, adoption, quality, and business impact.

Skills

Required

  • Demonstrated ability to deliver products or features in technical environments with multiple cross-functional stakeholders.
  • Bachelor's degree or equivalent
  • Strong execution skills and the ability to bring structure to ambiguous problems.
  • Experience writing product requirements, driving prioritization, and managing product development from concept to launch.
  • Strong communication skills, including the ability to synthesize complexity into clear recommendations and plans.
  • High ownership and willingness to dive into details where needed to move outcomes forward.

Nice to have

  • Experience working on products in autonomous vehicles, robotics, AI/ML industries or related technical domains.
  • Domain knowledge in at least one of the following pillars: sensor & compute integration, AI & ML systems, or evaluation & validation engines.
  • Comfort operating across software and hardware-adjacent problem spaces.

What the JD emphasized

  • hardest problem in AV today
  • unlocking real-world, long-tail driving data
  • data race
  • machine learning
  • semantic understanding
  • data & validation platforms
  • AI & ML systems
  • evaluation & validation engines

Other signals

  • unlocking real-world, long-tail driving data
  • data race
  • platforms that harness scale and real-world complexity
  • generate differentiated AV capabilities