Sr. Engineering Manager, Matching & Segmentation

Uber Uber · Consumer · San Francisco, CA · Engineering

Sr. Engineering Manager to lead multiple teams building and operating ML-powered matching, segmentation, and marketplace optimization systems at scale for Uber's mobility marketplace. The role involves defining technical vision, cross-functional partnership, and people management, with a focus on real-time algorithms and large-scale online experiments.

What you'd actually do

  1. Lead and grow multiple engineering teams building ML-powered matching, segmentation, and marketplace optimization systems and platform at scale.
  2. Define and drive the technical vision for your domain, aligning with broader Marketplace and company-level strategy.
  3. Partner cross-functionally with Product Management, Science, Operations, and peer engineering teams to prioritize, plan, and deliver high-impact initiatives.
  4. Coach and develop engineers at all levels, including Staff+ ICs and EMs, fostering a culture of technical excellence, ownership, and collaboration.
  5. Drive innovation in areas such as real-time matching algorithms, marketplace segmentation models, forecasting systems, and experiment-driven product development (e.g., Switchback experiments).

Skills

Required

  • software engineering experience
  • systems design
  • distributed systems
  • engineering management experience
  • leading multiple teams
  • managing managers
  • building and operating ML or optimization systems and platforms in production at scale
  • partner cross-functionally with Product, Science, and Business stakeholders
  • analytical and problem-solving skills
  • navigate ambiguous, high-impact problem spaces
  • BS in Computer Science or a related field

Nice to have

  • MS or PhD in Computer Science or a related field
  • marketplace systems
  • matching/ranking algorithms
  • large scale distributed systems
  • designing API for central services
  • scaling engineering organizations
  • developing senior technical talent
  • leading teams that run large-scale online experiments
  • data-driven product development
  • Strategic thinker
  • drive both technical and organizational innovation
  • managing geographically distributed teams

What the JD emphasized

  • ML-powered systems
  • scale
  • real-time matching algorithms
  • large-scale online experiments

Other signals

  • ML-powered systems
  • marketplace optimization
  • real-time decision-making
  • scale