Co Founder
I have developed structured datasets and annotation systems for training generative AI models, including creating taxonomies, labeling content, and conducting A/B testing to evaluate and rank AI-generated outputs for correctness, quality, and alignment with specifications. My work involves building annotation workflows, defining scoring criteria, and implementing quality control processes to ensure high data integrity. I am skilled in Python and LaTeX, and I bring a rigorous, detail-oriented approach to data labeling—especially for mathematical and technical domains. My experience also includes translating complex concepts into clear documentation, making me adept at both technical evaluation and communication.