Member of Managed workforces program
I worked as an AI contributor on the Outlier platform, where my main responsibility was to help improve language models using Supervised Fine-Tuning and Reinforcement Learning from Human Feedback . In SFT tasks, I created high-quality responses to given prompts, making sure they were accurate, clear, well-structured, and easy to understand. I carefully followed the provided guidelines and refined answers by improving grammar, clarity, and overall presentation so the model could learn from ideal examples. In RLHF tasks, I evaluated multiple AI-generated responses, compared them based on accuracy, relevance, clarity, and usefulness, and ranked them accordingly. I also provided detailed feedback explaining why one response was better than others, helping the model understand quality differences. Throughout my work, I maintained strong attention to detail, followed strict quality standards, and ensured consistency in all tasks. This experience helped me strengthen my analytical thinking and communication skills while contributing to the development of more accurate and reliable AI systems.