Annotation Quality Lead

About The Role

We’re looking for an Annotation Quality Lead to ensure that our labeled data meets the highest standards of accuracy, fairness, and contextual relevance. You’ll develop and uphold quality frameworks, lead audits and training programs, and collaborate across teams to shape data that powers safe, inclusive, and reliable AI.

What You’ll Do:

• Define and maintain quality standards, rubrics, and guidelines for annotation tasks
• Develop and manage gold-standard datasets that are accurate, inclusive, and culturally aware
• Lead review and audit processes, including double-blind reviews and inter-annotator agreement checks
• Analyze quality metrics and implement continuous improvement plans
• Facilitate feedback loops between annotators, domain experts, and stakeholders
• Design and deliver training, onboarding, and calibration programs
• Serve as the go-to person for annotation quality queries and dispute resolution
• Collaborate with operations, data, and research teams to align quality goals with project needs
• Ensure all annotation practices meet ethical, inclusive, and privacy standards
• Monitor edge cases, ambiguous data, and potential risks — and act on them swiftly

What We're Looking For:

• Bachelor's degree or equivalent experience in linguistics, quality assurance, data governance, or related fields. 
• 3–5 years' experience leading quality assurance in annotation projects, content moderation, or human-labeled data initiatives. 
• Proficiency with audit methodologies, annotation platforms, and inter-annotator agreement metrics. 
• Strong analytical, instructional, and stakeholder management capabilities. 
• Proficiency in Bahasa Melayu, with the ability to understand nuanced usage, cultural context, and formal writing structures.