Role Overview:
The Quality Control Coordinator for AI Data Annotation supports quality assurance processes to ensure annotated datasets meet defined guidelines and client standards. This role focuses on sampling, defect tracking, training coordination, documentation management, and audit readiness, playing a critical part in maintaining high-quality datasets for machine learning models.
Main Responsibilities:
- Perform sampling and quality checks on annotated datasets to ensure adherence to annotation guidelines
- Identify, log, and categorize annotation defects with severity levels, tracking corrective actions and rework tasks
- Coordinate onboarding training, calibration sessions, and refresher training for annotators and reviewers
- Maintain and update annotation guidelines, SOPs, and rubrics, ensuring proper version control and communication
Skills and Qualifications:
- Bachelor's degree in any discipline, with Data Science, Computer Science, Linguistics, or related fields preferred
- Strong understanding of annotation workflows such as bounding boxes, segmentation, classification, and transcription
- Proficiency in MS Excel or Google Sheets, including pivot tables, dashboards, and data analysis
- Excellent communication and coordination skills, with ability to work across cross-functional teams
Welo Data
Welo Data is a multilingual data and evaluation partner for foundation labs and enterprises deploying GenAI systems globally, delivering human judgment, data infrastructure, and evaluation systems for reliable AI performance across languages and cultures. It operates with a global network of over 500,000 vetted experts across 300+ languages, leveraging a unified model led by specialized experts with proprietary identity and fraud-prevention frameworks to ensure accurate and culturally grounded datasets.