Sr Program Manager, Tech- Data Labeling

Uber

  • Sunnyvale, CA
  • Permanent
  • Full-time
  • 1 month ago
As a Senior Program Manager - Data Labeling, you will lead cross-functional initiatives to build, scale, and optimize data annotation programs critical to AI model performance.You'll own program delivery across internal teams, vendor partners, and ML stakeholders to ensure high-quality labeled datasets are delivered on time and at scale.This role is both strategic and execution-driven: you'll define roadmaps, manage SLAs, create scalable processes, and resolve bottlenecks to ensure the labeling engine is efficient, quality-controlled, and model-aligned.What the Candidate Will Do:
  • 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.
Basic Qualifications:
  • 6+ years of program management experience, ideally in ML ops, data labeling, or AI infrastructure.
  • Proven track record managing multi-vendor operations or global labeling teams.
  • Strong understanding of ML lifecycle stages and the importance of annotated data quality.
  • Experience defining SOPs, audit mechanisms, and workflows for scalable data labeling.
  • Proficient in tools such as Jira, Asana, or Airtable for program tracking. In addition having deep understanding on ML Operations labelling tools is added advantage
  • Strong analytical and communication skills; ability to synthesise feedback from ML, ops, and product stakeholders.
Preferred Qualifications:
  • Exposure to LLMs, foundation models, or active learning-based data curation.
  • Familiarity with annotation for multimodal inputs (e.g., Audio, Video, Image, Text, Documents, OCR based forms etc)
  • Experience managing budgets, metrics, and KPIs across distributed teams.
  • Knowledge of quality scoring frameworks, inter-annotator agreement (IAA), or QA loop design.
  • Technical background (e.g., in ML, data science, or engineering) is a plus.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$162,000 per year - USD$180,000 per year.You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. You will also be eligible for various benefits. More details can be found at the following link .Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing .Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, Veteran Status, or any other characteristic protected by law.

Uber