Own the execution and delivery of AI data labeling programs across multiple clients and datasets
Build and maintain operational systems that support scalable project delivery
Establish operational frameworks that ensure consistent quality, efficiency, and throughput
Identify operational bottlenecks and implement improvements
Design operational playbooks for onboarding new projects and scaling existing ones
Oversee the full lifecycle of annotation programs from onboarding through delivery
Manage a portfolio of concurrent projects including pilot datasets and larger production programs
Coordinate across project managers, QA teams, and contributor networks
Monitor operational performance and proactively address delivery risks
Design and refine annotation workflows
Implement scalable quality assurance frameworks across annotation pipelines
Support the operational onboarding of new client programs
Track key operational metrics including throughput, quality performance, and delivery timelines
Guide and coordinate project managers and QA teams

6–10 years of experience in operations, program management, or delivery roles
Experience managing large-scale annotation programs involving distributed teams, contributor networks, and structured quality frameworks
Familiarity with multimodal datasets such as image, video, spatial, sensor, or language data
Excellent written and verbal communication skills
Strong understanding of how labeled datasets are used in machine learning pipelines
Experience using operational and project management tools such as ClickUp, Jira, Notion, or Airtable
Resourceful, adaptable, and comfortable operating in fast-moving environments

Operations Lead – AI Data Operations

Key skills