Data labeling
Evaluation of code generated by an LLM.
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I have hands-on experience in data labeling and AI training data, particularly in projects focused on evaluating large language models (LLMs). My work has included assessing code generation, STEM-related outputs in fields such as biology and physics, and text generation quality. Through platforms like Scale AI and Appen, as well as structured workflows in Excel and Google Sheets, I have developed a reliable process for reviewing outputs with precision and consistency. My strengths lie in accuracy, speed, and the ability to follow complex project guidelines while maintaining high standards of quality. With a background in coding, computer science, data analysis, and pharmaceutical sciences, I bring both technical expertise and domain knowledge that add value to AI training and evaluation tasks. This combination allows me to deliver thoughtful, detail-oriented assessments that support the development of more capable and reliable AI systems.
Evaluation of code generated by an LLM.
Certificate, Single Variable Calculus
Certificate, Machine Learning
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