Mahmoud Salem
AI ML at Google
Old Toronto, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolMahmoud Salem is an AI/ML researcher and engineer with nine years of experience building and optimizing large language models and multimodal systems, currently contributing to GenAI at Google. He holds an MSc in Artificial Intelligence from the University of Guelph and is a Vector Institute scholar with multiple research awards and peer-reviewed publications in model efficiency and training. At Cerebras he led efforts on training and fine-tuning foundational models across languages and co-authored recent arXiv papers on LLM optimization, while earlier internships at Google, Borealis, and Samsung sharpened his language-modeling and applied research skills. Mahmoud also contributes practical tooling to the community—maintaining a TensorFlow project-template that encapsulates best practices for model architecture, training loops, and experiment management. Comfortable bridging deep research and production constraints, he combines rigorous academic grounding with hands-on experience training large-scale models on cutting-edge hardware.
9 years of coding experience
7 years of employment as a software developer
Master's degree Artificial Intelligence, Master's degree Artificial Intelligence at University of GuelphBachelor of Science - BS Computer Engineering, Bachelor of Science - BS Computer Engineering at Cairo University
English
Stackoverflow
143reputation
7kreached
6answers
1question
Github Skills (18)
deep-learning10
tensorflow10
neural-network10
oop9
python9
guideline8
model-building8
template-engine7
templater7
computer-engineering7
template-tags7
keras6
lstm6
machine-learning6
append6
Programming languages (2)
Github contributions (5)
MrGemy95/Tensorflow-Project-Template
Jan 2018 - Nov 2018
A best practice for tensorflow project template architecture.
Role in this project:
ML Engineer
ML EngineerContributions:88 commits, 13 PRs, 38 pushes in 9 months
Contributions summary:Mahmoud primarily focused on setting up the foundational elements of a TensorFlow-based project, including core classes for model building, training, and logging. Their commits demonstrate an understanding of model architecture, training loops, and experiment management. Key contributions include defining base classes and implementing a basic example model, which sets the stage for more complex deep learning projects within the repository's framework.
best-practicetemplatepythonmlpdeep-learning
MrGemy95/DL-Playground
Mar 2017 - Feb 2018
Contributions:46 commits, 19 pushes, 1 comment in 11 months
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