Qc Coordinator (Europe/America Based) (Argentina), Florencio Varela

Role OverviewThe QC Coordinator for AI Data Annotation supports quality assurance processes to ensure annotated datasets meet defined guidelines and client standards. The role focuses on sampling, defect tracking, training coordination, documentation management, and audit readiness. This position plays a key role in maintaining data quality critical for training and evaluating machine learning models.Key ResponsibilitiesPerform sampling and quality checks on annotated datasets (text, image, audio, or video) to ensure adherence to annotation guidelines.Identify, log, and categorize annotation defects (e.g., labeling errors, boundary issues, misclassification) with severity levels.Track corrective actions and rework tasks to closure; validate re‐tests and document outcomes.Coordinate onboarding training, calibration sessions, and periodic refreshers for annotators and reviewers.Ensure annotation guidelines, SOPs, and rubrics are updated, version‐controlled, and clearly communicated to stakeholders.Identify process gaps and recommend practical improvements (annotation templates, QA checklists, sampling strategies). Manage access permissions for annotation tools, QA platforms, and shared repositories.Required Skills and QualificationsBachelor degree in any discipline (Data Science, Computer Science, Linguistics, or related fields preferred).2–4 years of experience in Quality Control/Quality Assurance within AI data annotation, data labeling, or content moderation.Strong understanding of annotation workflows (bounding boxes, segmentation, classification, transcription, etc.). Familiarity with QA metrics such as accuracy, F1 score, precision/recall, and inter‐annotator agreement. #J-*****-Ljbffr Postúlate en Kit Empleo: kitempleo.com.ar/empleo/qj3au