Description
Manage and support a team of Quality Engineers responsible for QA strategy, tooling, and implementation across annotation workflows. Define and refine scalable processes and metrics to assess the quality, consistency, and relevance of labeled data. Partner with Engineering teams to build automated validation logic for detecting inconsistencies and data anomalies. Collaborate with Data Scientists and ML Engineers to analyze how data quality impacts model behavior and identify opportunities for data improvement. Lead multi-functional alignment on annotation QA standards and ensure feedback loops between quality, guidelines, and tooling. Own and evolve golden set evaluations, consensus grading protocols, and annotator quality tracking mechanisms. Conduct root cause analyses on quality issues and drive corrective actions in collaboration with upstream teams. Stay ahead of QA and data quality best practices, and drive continuous improvement in tools and methodologies.