Mohammad Mahbubuzzaman
Senior Machine Learning Engineer at Meta
Newark, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMohammad Mahbubuzzaman is a Senior Machine Learning Engineer with nine years of experience building and optimizing production ML systems for ads, compiler stacks, and embedded AI across leaders like Meta, Amazon, NVIDIA, and Intel. He blends deep compiler and performance expertise—working on projects such as Intel/Nervana's nGraph and NVIDIA’s Orin compiler—with large-scale ML pipeline design using Spark, GPU clusters, and AWS for ads ranking and retrieval. Known for driving performance programs and shipping compiler-level optimizations, he spans the stack from model architecture to silicon-level cycles and watts. He also contributes to open-source C++ deep learning tooling, adding provenance tracking and rigorous unit tests to nGraph, reflecting a practical focus on correctness and traceability. Based in Newark, CA, he pairs technical leadership with hands-on engineering to make cost- and power-efficient ML solutions for real-world systems.
9 years of coding experience
17 years of employment as a software developer
Master of Science (M.Sc.) Computer Science, Master of Science (M.Sc.) Computer Science at North Carolina State UniversityBSC Computer Science and Engineering, BSC Computer Science and Engineering at Bangladesh University of Engineering and TechnologyGraduate Certificate Artificial Intelligence, Graduate Certificate Artificial Intelligence at Stanford University
Stackoverflow
220reputation
66kreached
9answers
1question
Github Skills (12)
unit-testing10
graph10
c-language10
cprogramming-language10
graph-theory10
probability6
asp-net6
machine-learning6
tdd6
loops6
classification6
linq6
Programming languages (4)
Github contributions (5)
NervanaSystems/ngraph
Mar 2019 - Oct 2019
nGraph - open source C++ library, compiler and runtime for Deep Learning
Role in this project:
Back-end Developer
Back-end DeveloperContributions:9 commits, 12 PRs, 40 pushes in 7 months
Contributions summary:Mohammad primarily focused on adding and refining provenance tracking capabilities within the nGraph library. Their contributions involved implementing features to add, remove, and propagate provenance tags across nodes during graph operations. They also added unit tests to verify the provenance functionality, including testing node replacement scenarios. Furthermore, the user addressed code style issues and fixed header include errors.
inference-enginecppc-librarydeep-learningtvm
tachyon77/LeetCode
Oct 2017 - Feb 2018
Contributions:56 pushes, 1 branch in 4 months
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