Sr Staff ML Engineer - Applied AI

Uber Uber · Consumer · San Francisco, CA · Engineering

The Applied AI team at Uber is seeking a Sr Staff ML Engineer to define the multi-year technical vision and architecture for foundation models powering discovery experiences across Mobility and Delivery. This role will focus on building a common semantic backbone for understanding users, places, merchants, items, and behavioral patterns, which will power personalization, search, agents, automation, and decision systems. The engineer will set long-term technical direction, drive alignment on strategy, and deliver measurable impact at global scale.

What you'd actually do

  1. Define and champion the multi-year technical vision and architecture for foundation models across Search, Recommendations, and Conversational AI.
  2. Set the architectural standard and drive system design for critical, high-leverage ML platforms across Mobility and Delivery.
  3. Lead cross-team initiatives spanning Retrieval, Ranking, Personalization, and LLM-powered assistants, resolving complex technical trade-offs across organizational boundaries.
  4. Define long-term investment areas (build vs fine-tune vs partner models) with clear business rationale and long-term viability.
  5. Provide principal-level technical leadership, mentoring Staff and Senior Staff engineers, and setting the bar for technical excellence across the entire AI organization.

Skills

Required

  • Masters degree or Ph.D in Computer Science, Engineering, Mathematics
  • 12+ years of ML experience
  • large-scale deep learning systems
  • high-impact ML systems in search, recommendations, or conversational AI
  • transformers
  • retrieval systems
  • ranking
  • embedding architectures
  • PyTorch
  • distributed training
  • technical strategy for a large organization
  • influence product roadmaps at the executive level
  • product intuition
  • connect model improvements to business outcomes

Nice to have

  • Track record of successfully launching multi-year, multi-org ML initiatives that drove step-change business outcomes
  • Successfully championed and driven the adoption of multi-year technical roadmaps across multiple large engineering organizations
  • Elevated engineering standards through mentorship and technical leadership, establishing org-wide best practices

What the JD emphasized

  • multi-year technical vision and architecture
  • foundation models
  • common semantic backbone
  • continuously improving it with cross-LOB signals
  • intelligence compounds rather than fragments
  • personalization, search, agents, automation, and decision systems
  • set the long-term technical direction for the organization
  • drive alignment on product and engineering strategy at the executive level
  • deliver step-change measurable impact at global scale
  • Masters degree or Ph.D in Computer Science, Engineering, Mathematics
  • 12+ years of ML experience
  • large-scale deep learning systems
  • high-impact ML systems
  • Deep expertise in transformers, retrieval systems, ranking, and embedding architectures
  • Strong experience with PyTorch and distributed training
  • Proven ability to set the technical strategy for a large organization and influence product roadmaps at the executive level
  • Strong product intuition and ability to connect model improvements to business outcomes
  • Track record of successfully launching multi-year, multi-org ML initiatives that drove step-change business outcomes
  • Successfully championed and driven the adoption of multi-year technical roadmaps across multiple large engineering organizations
  • Elevated engineering standards through mentorship and technical leadership, establishing org-wide best practices

Other signals

  • foundation models
  • semantic backbone
  • personalization
  • search
  • conversational AI
  • LLM-powered assistants