Senior Engineering Manager - (machine Learning) Uber Eats

Uber Uber · Consumer · New York, NY +2 · Engineering

Senior Engineering Manager for Uber Eats Shopping ML team, focusing on personalization and discovery experiences. The role involves defining strategy, collaborating with cross-functional teams, developing scalable ML systems, and staying updated on industry trends. Requires significant experience in managing ML teams and applying ML to real-world problems, particularly in consumer-facing products.

What you'd actually do

  1. Define and execute the Shopping ML product and engineering roadmap and strategy, focusing on personalization and discovery experiences that enhance multiple surfaces on the Uber Eats app including the store, checkout, and s experiences.
  2. Collaborate with product managers, data scientists, designers, and operations to identify opportunities, prioritize initiatives, and deliver ML-powered features that feel intuitive and assistive.
  3. Develop scalable systems that help consumers easily discover and order food and groceries, while also surfacing personalized recommendations for future meals or unmet needs.
  4. Partner with other product & engineering teams to ensure ML frameworks and capabilities are leveraged to create cohesive, delightful user experiences.
  5. Stay on top of industry trends and emerging best practices in machine learning and personalization to ensure Uber Eats continues to lead in innovation.

Skills

Required

  • MS or equivalent experience in Computer Science, Engineering, Mathematics, or related field
  • 10+ years of industry experience in software engineering and AI/ML
  • 5+ years of experience directly managing engineering or ML teams, with a track record of hiring, mentoring, and growing high-performance teams
  • Deep understanding of machine learning fundamentals, with practical experience applying them to real-world problems.
  • Experience working with cross-functional teams (product, science, product ops, etc.)

Nice to have

  • Experience leading team of teams through other managers
  • PhD in Machine Learning, Computer Science, Statistics, or a related field with research or applied focus on large-scale ML systems.
  • Experience in consumer-facing products, with a focus on personalization, content recommendation, and understanding user context to create tailored experiences
  • Demonstrated ability to align technical investments with high-impact use cases and broader business objectives
  • Experience crafting an ML-first vision, identifying machine learning needs across multiple products, and proposing solutions that serve long-term user and business needs
  • Proven ability to navigate a diverse set of opinions among cross-functional teams, synthesize different perspectives, and drive decisions effectively
  • Strong communication skills, with the ability to articulate complex ideas clearly to both technical and non-technical audiences

What the JD emphasized

  • directly managing engineering or ML teams
  • personalization
  • recommendation

Other signals

  • personalization
  • recommendation systems
  • ML-powered features
  • scalable systems