Director, Engineering - Av Labs

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

Director of Engineering role focused on leading the development of AI models, algorithms, and semantic engines for Uber's autonomous vehicle data capabilities. The role involves building advanced AI foundation models and scalable algorithms that process multi-modal sensor data to enrich L4 data and evaluation engines for autonomous driving.

What you'd actually do

  1. Build, scale, and lead a high-performing engineering organization comprising AI modeling, machine learning, and autonomy engineers.
  2. Provide the overarching technical vision for the AI models and autonomy algorithms that enrich our L4 data lake.
  3. Oversee the development of cutting-edge AI models and semantic data processing algorithms.
  4. Act as a critical leader within AV Labs, partnering closely with Product, Operations, and other Uber executives to align AI model development and algorithmic architecture with business goals

Skills

Required

  • 12+ years of engineering experience in AI modeling, applied ML, or Autonomous Systems
  • 5+ years of experience managing engineering teams, including experience managing managers and leading large-scale ML/AI engineering organizations
  • Proven track record of delivering highly scalable algorithms, advanced AI models, and large-scale ML solutions from conception to production
  • Bachelor's degree in Computer Science, Computer Engineering, or related fields

Nice to have

  • Advanced degree (MS or PhD) in Computer Science, Machine Learning, Robotics, or a related field
  • Deep understanding of AI foundation models, modern ML architectures, and large-scale data processing for model training
  • Prior experience in the Autonomous Vehicle (AV) industry, specifically related to offline evaluation, simulation, or autonomous data mining
  • Strong background in building models and algorithms that process, structure, and query massive datasets to enable advanced machine learning and scene understanding
  • Demonstrated ability to drive technical strategy and influence cross-functional roadmaps in a highly matrixed, fast-paced organization

What the JD emphasized

  • delivering highly scalable algorithms, advanced AI models, and large-scale ML solutions from conception to production
  • building models and algorithms that process, structure, and query massive datasets to enable advanced machine learning and scene understanding

Other signals

  • leading AI/ML teams
  • building foundation models
  • processing multi-modal sensor data
  • autonomous driving data