At Hugo Technologies, I audit AI-generated responses across LLM evaluation workflows, assessing accuracy, relevance, consistency, and compliance with quality standards. I analyze recurring errors and provide structured feedback to support annotation consistency and guideline adherence.
Previously, I annotated and validated AI/ML data across speech, audio, transcription, and search relevance workflows at Hugo Technologies, and labeled machine-learning data for Pallon. I also supported quality alignment, escalated ambiguous cases, and worked with project teams to address data-quality gaps.

