Divine Ifeanyi

I am an AI Data and Operations Specialist with experience across AI training data, data annotation, AI evaluation, and quality review workflows. I have reviewed thousands of AI training data submissions for Outlier AI across text, image, and multimodal datasets, applying project guidelines, quality rubrics, and acceptance criteria to improve dataset quality and AI output reliability.

My experience across Outlier AI, Remotasks, Atlas Capture, TELUS International AI, and Appen includes AI-generated content evaluation, annotation quality review, image and video labeling, dataset validation, error identification, correction, and providing clear written feedback to improve AI systems. I specialize in human-in-the-loop AI workflows, quality assurance, and ensuring AI outputs meet defined standards.

My background combines hands-on AI project experience, quality-focused review practices, and a strong interest in AI operations, knowledge management, and responsible AI improvement. I am passionate about helping organizations use AI effectively through reliable workflows, accurate information, structured evaluation, and continuous quality improvement.