At Appen, uTest, and Test.io, I annotated image, text, audio, and video data for AI training projects, following project guidelines and quality standards. I reviewed submissions for accuracy, consistency, and completeness, and reported defects and edge cases with reproducible notes.
On my 2026 multi-modal annotation project, I completed sentiment analysis and named entity recognition tasks, segmented audio for transcription, and tracked objects frame by frame in video. I configured custom labeling schemas and interfaces in Label Studio.
I also built an AI customer support email triage workflow using Gmail, Make.com, and Google Gemini. It classifies incoming requests and creates labeled Gmail drafts, using a constrained prompt to return one of three categories.
My background includes a B.Sc. in Computer Science and Mathematics and training in data labeling, HITL QA, LLM fine-tuning, prompt engineering, and model evaluation. I’ve also performed software QA testing through uTest and Test.io and handled contract logistics and documentation in the financial services sector.
