About the Role
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 .