Ahmed Khamis
Senior Applied Machine Learning Scientist at Cision
Egypt
Summary
🤩
Rockstar🎓
Top SchoolAhmed Khamis is a Senior Applied Machine Learning Scientist with six years of experience building large-scale NLP and neural systems, currently driving LLM, translation, and summarization efforts at Cision. He has a track record of production impact—leading models that saved $80k+ monthly—and pretraining and fine-tuning domain-specific LLMs for complex NLP pipelines. Prior roles include optimizing speech-to-text, multilingual/multi-task classifiers, topic and NER models, and speeding up ML pipelines (KubeFlow) at Factmata and Cision. An active open-source contributor and former GSoC maintainer for PyTorch-Ignite, he implemented distributed-ready metrics (including Cohen’s Kappa) and boosted test coverage to near 96%. A Georgia Tech MS (Computer Science, ML specialization) candidate based in Egypt, he blends research rigor with hands-on engineering and mentorship across cross-functional teams. Notably, he contributed benchmarking work for GPT-4 in robotics modalities, collecting observations across 54 datasets—showing a practical knack for organizing complex, multi-domain research efforts.
6 years of coding experience
3 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Georgia Institute of TechnologyBachelor's degree, Computer Science, Bachelor's degree, Computer Science at Fayoum University
Arabic, English, German
Github Skills (9)
pytorch10
machine-learning10
pytest10
python10
metric10
testing10
deep-learning9
mask-rcnn4
faster-rcnn4
Programming languages (7)
Github contributions (5)
pytorch/ignite
Feb 2021 - Nov 2021
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
Role in this project:
ML Engineer & QA Engineer
ML Engineer & QA EngineerContributions:234 reviews, 78 commits, 92 PRs in 8 months
Contributions summary:Ahmed primarily contributed to the implementation and testing of new metrics, specifically Cohen's Kappa and related functionalities within the PyTorch Ignite library. Their work involved adding the Cohen's Kappa metric, integrating comprehensive tests to ensure its correctness and robustness. Furthermore, they were responsible for fixing various test issues and adding unit tests to ensure the robustness of new features and the general reliability of the library.
pytorchpythondeep-learninghigh-levelneural-networks
KickItLikeShika/Neural-Network
Jul 2020 - Dec 2020
Contributions:72 commits, 72 pushes, 1 branch in 5 months
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