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Appen
Clickworker
Data Annotation Tech
Labelbox
Mercor
OneForma
TelusNo subject matter listed
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VideoI have developed extensive expertise in data labeling and AI training data through significant roles with both Appen Global and TELUS International. At Appen, I reviewed and annotated between 600 and 700 short-form video posts each week across platforms like TikTok, Instagram Reels, and YouTube Shorts. My average annotation accuracy was 99.1%, which surpassed the team benchmark, and I proactively identified and recategorized over 3,200 mislabeled assets during quality assurance sweeps. These efforts increased dataset precision and directly improved large AI model F1 scores. I also authored twelve quick-reference guides to help evaluator teams address challenging edge cases including satire, medical misinformation, and nuanced hate speech, supporting the work of a forty-member team. At TELUS International, I analyzed and rated 200 to 250 healthcare-related Google queries daily for large language model finetuning, meticulously applying rubrics to evaluate accuracy, helpfulness, and medical safety. I maintained 100% compliance in flagging sensitive or safety-critical content and achieved a flawless safety record over two years by effectively identifying privacy issues, self-harm risk, and potential misinformation. My ability to ensure labeling accuracy, apply rigorous quality standards, and foster teamwork reflects my core strengths as a detail-oriented, adaptive, and self-driven contributor to effective AI training data and annotation projects.
I perform A/B testing by evaluating and comparing model outputs, selecting the most accurate and optimal responses from multiple AI systems to ensure continuous improvement and alignment with project objectives.
I record high-quality audio prompts and responses for SFT training, using a wide range of voice acting techniques and emotions to create diverse, natural-sounding datasets that enhance AI model performance and conversational realism.
At TELUS International, I analyzed and rated hundreds of healthcare-related Google queries each day for large language model finetuning, evaluated content for accuracy and safety, and consistently flagged privacy or safety issues with perfect compliance, ensuring no critical incidents throughout my tenure.
At Appen Global, I reviewed and annotated hundreds of short-form social media videos, maintained a 99.1% annotation accuracy, recategorized mislabeled assets to improve dataset quality, and authored guides for evaluating complex content cases. My work contributed directly to more accurate, reliable AI and multimedia model training data.
Secondary School Diploma, General Education
Freelance Writer
Data Solutions Analyst
