I am a Senior Software Engineer at Meta with over 12 years of experience building large-scale AI systems and evaluation infrastructure. In my current role, I work closely with Research Scientists and Applied Scientists, contributing to the design, evaluation, and deployment of production-grade AI systems and data-driven platforms.
I regularly review internal machine learning and AI research papers, assessing experimental design, methodological rigor, statistical validity, and reproducibility. My work involves evaluating the strength of empirical evidence, the soundness of reasoning-related claims, and the clarity of problem formulation and benchmarking methodology. I have experience examining multi-step evaluation frameworks, dataset quality, and consistency in experimental reporting.
Through this experience, I have developed a strong ability to assess whether a submission presents a genuine methodological or empirical contribution, ensuring that claims are well-supported, statistically sound, and clearly articulated.
