Divine-Joy

about

I am an AI training and evaluation specialist with over four years of experience supporting LLM improvement, data annotation, quality assurance, and multimodal dataset development. I evaluate and rank AI-generated outputs using detailed rubrics for factual accuracy, instruction following, safety, helpfulness, tone, and logical coherence. I am experienced in RLHF workflows, preference evaluation, adversarial prompt testing, and identifying hallucinations or inconsistencies in model responses. Also, I have experience breaking down software workflows, which makes spotting UI/UX bugs and usability friction points second nature for me. I also work across UI/UX, text, image, video, and audio annotation projects, including ground-truth development, timestamped video and audio segmentation, transcription, entity labeling, image-to-text tasks, e-commerce content QA, and content moderation. I follow complex guidelines closely, perform self and peer QA, and collaborate with teams to improve annotation consistency and inter-rater reliability. In addition, I provide Igbo and English linguistic validation and transcription support for AI training datasets. I am comfortable using tools such as GPT-4o, Claude, Gemini, DeepSeek, Perplexity, Excel, Python, SQL, Jira, Notion, and Power BI. I bring strong analytical judgment, attention to detail, research skills, and reliable delivery under quality and turnaround requirements.