David Aponte is a Senior Research SDE in Microsoft’s Applied Sciences Group with eight years of experience building efficient training and inference methods for deep learning, focused on quantization, pruning, distillation, sparsity, and parallelism. Based in New York, he applies ML systems expertise to audio/visual perception problems and bridges research and production from his prior senior engineering and MLOps roles. His background spans academia and industry—research affiliate work at UIUC, MLOps community organizing, and ML engineering at BenevolentAI—highlighting both reproducible research and production-grade infrastructure. Trained across computer science, data science, education, and molecular biology, he brings a multidisciplinary perspective that often surfaces practical, systems-level optimizations not obvious from model papers alone.
8 years of coding experience
4 years of employment as a software developer
Computer Science, Computer Science at New Jersey Institute of Technology
Master of Science - MS, Data Science, Master of Science - MS, Data Science at Merrimack College
Master of Science - MS, Secondary Education and Teaching, Master of Science - MS, Secondary Education and Teaching at University of Bridgeport
Bachelor of Science - BS, Molecular Biology, Bachelor of Science - BS, Molecular Biology at Montclair State University
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