Summary
M Saiful Bari (Maruf) is an applied scientist with eight years of experience specializing in pretraining anatomy, LLM alignment, and robust evaluation of frontier models. He has driven multilingual pretraining and post-training for large models at AWS and led core LLM training and alignment work (ALLaM) at SDAIA, earning an MIT TR35 award for that effort. His PhD research focused on transfer learning for neural models, and he contributed to BLOOM’s architecture, pretraining, and prompt engineering. Multiple internships at AWS honed his expertise in parameter-efficient multi-task inference and cross-lingual few-shot adaptation. Based in Sunnyvale, he pairs deep research credentials from NTU and IUT with practical production experience shipping Nova-series multilingual models. He often emphasizes that “an algorithm must be seen to be believed,” reflecting a bias toward empirical, demonstrable results.
8 years of coding experience
8 years of employment as a software developer
Bachelor’s Degree Computer Science and Enginnering, Bachelor’s Degree Computer Science and Enginnering at Islamic University of Technology
High School National Curriculum given by government, High School National Curriculum given by government at Government Laboratory High School
Associate’s Degree Science, Associate’s Degree Science at Dhaka City College
Ph.D. Candidate Computer Science, Ph.D. Candidate Computer Science at Nanyang Technological University Singapore
English, Bangla