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Sr. Program Manager, AI Data Operations

United States, San Francisco 167000.00 - 185500.00 USD / Year · Job Posted January 29, 2026
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Job Description

Uber AI Solutions is one of Uber’s biggest bets with the ambition to build one of the world’s largest data foundries for AI applications and evolve into a platform of choice for a variety of online tasks. AI Data Labelling operations is one of the core functional teams within Uber AI Solutions with the responsibility to oversee the end-to-end lifecycle of the data annotation programs for B2B clients.

Job Responsibility

  • Define the programs and its key objectives to support LLM model training
  • Drive cross-functional efforts across Operations, Product, Eng and Legal to define the Program-level Ops strategy
  • Define scalable data labeling workflows leveraging internal tools, external vendors, and automation
  • Shape task/ product/ feature launches and improvements
  • Lead cross-functional initiatives to build, scale, and optimize data annotation programs
  • Own program delivery across internal teams, vendor partners, and ML stakeholders
  • Define roadmaps, manage SLAs, create scalable processes, and resolve bottlenecks
  • Operational excellence - Define and drive end-to-end execution of large-scale annotation programs across multiple data types
  • Collaborate with ML, product, and data operations teams to scope and prioritize labeling needs
  • Own vendor engagement: onboarding, SLA management, training, and quality reviews
  • Build feedback loops between annotators and model performance to inform labeling strategies
  • Create dashboards and reporting mechanisms to track labeling velocity, quality, and cost
  • Lead initiatives to improve labeling efficiency through tooling enhancements and process automation
  • Be the voice of labeling in cross-functional forums—translating model needs into operational plans
  • Customer engagement - Drive daily, weekly and monthly meetings, business reviews and reports

Requirements

  • 7+ years of program management experience, ideally in ML ops, data labeling, or human data operations
  • Proven track record managing multi-vendor operations or global labeling teams
  • Strong understanding of AI/ML lifecycle stages and the importance of annotated data quality
  • Experience defining SOPs, rubrics, audit mechanisms, and workflows for scalable data labeling
  • Proficient in project management tools
  • Strong analytical and communication skills
  • ability to synthesize feedback from ML, ops, and product stakeholders

Nice to have

  • Exposure to LLMs, foundation model training and human in the loop (HITL) operations
  • Familiarity with annotation for multimodal inputs (e.g., Audio, Video, Image, Text, Documents, OCR based forms etc)
  • Experience of working in customer facing roles
  • Experience managing budgets, metrics, and KPIs across distributed teams
  • Knowledge of quality scoring frameworks, defining quality rubrics and QA loop design
  • Technical background (e.g., in ML, data science, or engineering) is a plus

What we offer

  • Eligible to participate in Uber's bonus program
  • May be offered an equity award & other types of comp
  • Eligible for various benefits

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