Serve as a Subject Matter Expert (SME) for high-complexity labeling workflows, ensuring data integrity for machine learning models and AI safety programs. Conduct deep-dive quality audits and Root Cause Analysis (RCA) to identify labeling discrepancies, providing actionable metrics to cross-functional stakeholders. Collaborate with global vendor partners to resolve technical and policy blockers, optimizing program quality through detailed process documentation and post-mortems. Bridge the gap between raw data sets and engineering requirements by refining labeling guidelines and presenting insights in weekly business reviews.

Train and evaluate expressive speech datasets for AI models, focusing on linguistic accuracy and cultural nuance. Execute QA/QC on multilingual audio assets to ensure emotional consistency and high-fidelity output. Deliver technical feedback to engineering teams to refine dataset usability for global applications.

Verified EN-US audio annotations and metadata integrity for production-ready ASR applications. Ensured 100% adherence to formatting and quality standards for speech-to-text data pipelines.

Paused professional work to provide full-time medical support for a family member.

• Managed over 300 projects annually with external vendors and internal translators, ensuring timely and high-quality completion.

• Successfully translated over 20,000 words monthly for marketing and legal content.

• Monitored deliverables, addressed project creep, and collaborated with stakeholders to meet predetermined deadlines.