University of Ibadan
B.s.c., computer science
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My experience in AI training data is built on a foundation of high-density RLHF (Reinforcement Learning from Human Feedback) and Supervised Fine-Tuning (SFT). I specialize in the "Goldilocks" zone of data labeling—where the goal isn't just to categorize, but to refine complex reasoning, creative nuance, and factual precision. I have extensive experience in multi-turn dialogue evaluation, where I rank and rewrite model outputs to improve tone consistency, logical flow, and safety compliance. By focusing on high-signal data rather than high-volume noise, I help bridge the gap between raw model capabilities and helpful, human-aligned interactions. What sets me apart is a rigorous approach to "Red Teaming" and hallucination detection. I don’t just identify when a model is wrong; I can pinpoint the specific logical failure or data bias that led to the error. My skillset includes complex prompt engineering to stress-test model boundaries and the ability to synthesize technical information into clear, accessible prose. Whether it is auditing code snippets for efficiency or fine-tuning the empathetic resonance of a persona, I provide the granular feedback necessary to evolve a model from a simple predictive engine into a truly sophisticated collaborator.
Michael A. hasn’t added any AI Training or Data Labeling experience to their OpenTrain profile yet.
B.s.c., computer science
AI Data Trainer & Annotation Specialist