[Hiring] AI Data Quality Control Coordinator @Welo Global

Role Description

The Quality Control Coordinator for AI Data Annotation is responsible for supporting 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.

The position plays a critical role in maintaining high-quality datasets used for training and evaluating machine learning models, working closely with operations, project managers, and annotation teams.

Main Responsibilities

• Perform sampling and quality checks on annotated datasets (text, image, audio, 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 refresher training for annotators and reviewers.
• Maintain and update annotation guidelines, SOPs, and rubrics, ensuring proper version control and communication.
• Prepare client-ready quality reports, including tables, charts, and summaries, with consistent formatting.
• Liaise with Project Managers and Operations teams to align timelines, reporting, and audit requirements.
• Manage access permissions for annotation tools, QA platforms, and shared repositories.
• Support vendor coordination, including documentation requests, SLAs, and quality expectations.
• Identify process gaps and recommend practical improvements (e.g., templates, QA checklists, sampling approaches).

Qualifications

• Bachelor’s degree in any discipline (Data Science, Computer Science, Linguistics, or related fields preferred).
• Strong understanding of annotation workflows (bounding boxes, segmentation, classification, transcription, etc.).
• Familiarity with QA metrics such as accuracy, precision/recall, F1 score, and inter-annotator agreement.
• Proficiency in MS Excel or Google Sheets (pivot tables, dashboards, data analysis).
• Strong attention to detail and ability to identify subtle quality issues in datasets.
• Excellent communication and coordination skills, with the ability to work across cross-functional teams.
• Strong organizational skills and ability to manage multiple priorities in a fast-paced environment.

Requirements

• 2–4 years of experience in Quality Control/Quality Assurance within AI data annotation, data labeling, or content moderation.
• Experience working with annotation tools (e.g., Labelbox, CVAT, Scale AI, or similar platforms).
• Exposure to NLP, Computer Vision, or Speech datasets.
• Basic understanding of machine learning workflows and data lifecycle.
• Experience working with global clients and distributed or remote annotation teams.

Benefits

This freelance role offers an exciting opportunity to contribute to cutting-edge AI projects while building expertise in data quality and annotation processes. Join us to play a key role in shaping high-quality datasets that power intelligent systems.

Company Description

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.