Senior Prompt Reviewer / AI Trainer
I have hands-on experience in AI training data and data labeling through platforms like Handshake AI, Outlier, and DataAnnotation, where I’ve worked on improving model performance across a range of tasks including text classification, prompt evaluation, response ranking, and annotation for LLM fine-tuning. My work has focused on ensuring high-quality, structured datasets by applying consistent labeling standards, identifying edge cases, and refining outputs to align with model objectives. I’ve also contributed to prompt engineering and evaluation workflows, helping optimize how AI systems interpret and generate responses in real-world scenarios. What sets me apart is my ability to think both analytically and systemically. I don’t just label data, I look at the “why” behind it, identifying patterns, inconsistencies, and opportunities to improve the overall pipeline. With a background in recruiting and process optimization, I bring strong attention to detail, efficiency, and quality control, along with experience working with AI tools, automation workflows, and data systems. This allows me to contribute beyond task execution, supporting scalable, high-impact improvements in AI training processes.