Senior Engineering Manager, Av Labs

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

Senior Engineering Manager for Uber's AV Labs, leading a team focused on AI models and behavioral causality for autonomous driving data. The role involves building and managing ML engineers and researchers to develop foundation models for complex urban edge cases, enriching L4 data lake with semantic meaning from multi-modal sensor data, and contributing to the L4 data and evaluation engine.

What you'd actually do

  1. Build, manage, and mentor a high-performing engineering team of ML experts, AI modelers, and data scientists.
  2. Drive the day-to-day development of advanced autonomy algorithms and foundation models.
  3. Collaborate with technical leadership to steer foundational architectural choices.
  4. Partner closely with Directors, Principal Engineers, Product Managers, and infrastructure teams to align your team's ML modeling efforts with broader business goals and ensure seamless deployment at scale.

Skills

Required

  • 8+ years of software engineering experience in applied ML, AI modeling, or Autonomous Systems.
  • 3+ years of experience managing engineering teams, with a track record of leading high-performing ML or AI organizations.
  • Proven experience delivering complex, large-scale AI models or ML pipelines from conception to production.
  • Deep expertise in modern AI/ML frameworks (e.g., PyTorch, TensorFlow) and Python/Linux environments.

Nice to have

  • Advanced degree (MS or PhD) in Robotics, Machine Learning, Computer Vision, or a related field.
  • Deep technical understanding of AI foundation models, multi-modal perception, and causal behavior modeling.
  • Prior experience in the Autonomous Vehicle (AV) industry, specifically focused on offline evaluation, 3P data understanding, or autonomous data mining (as opposed to embedded on-car execution).
  • Strong background in guiding teams to build models that process, structure, and query massive datasets to enable advanced scene representation.
  • Excellent communication skills with the ability to translate complex technical concepts into strategic roadmaps for cross-functional partners.

What the JD emphasized

  • high-velocity team
  • hardest problem in AV today
  • unlocking real-world, long-tail driving data
  • data race
  • AI models and behavioral causality
  • foundation models
  • complex urban edge cases
  • L4 data and evaluation engine
  • ultimate data mining platform
  • high-fidelity semantic meaning
  • multi-modal sensor data
  • massive driving data
  • large scale data
  • offline evaluation
  • autonomous data mining

Other signals

  • unlocking real-world, long-tail driving data
  • foundation models that parse complex urban edge cases
  • L4 data and evaluation engine
  • data mining platform for our autonomous partners