Ziad Amerr
Machine Learning & Quality Assurance Engineer at Siemens EDA (Siemens Digital Industries Software)
Cairo, Cairo, Egypt
Summary
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Rockstar🎓
Top SchoolZiad Amerr is a Machine Learning and Quality Assurance Engineer based in Cairo with four years of hands-on experience building and validating ML systems at Siemens EDA. He specializes in teaching language models and reducing model errors, blending ML engineering with rigorous testing and QA practices. An active open-source contributor, he implemented and tested loss functions and backend utilities in the Ivy framework, improving cross-framework compatibility for Torch, NumPy, and JAX. His background spans internships and roles focused on ML optimization, and he brings practical full-stack and filmmaking experience that sharpens his sense for product-quality and user-facing behavior. Colleagues describe him as pragmatic and detail-oriented, comfortable moving models from research prototypes toward reliable production systems.
3 years of coding experience
4 years of employment as a software developer
Bachelor of Engineering - BE, Bachelor of Engineering - BE at Ain Shams UniversityBachelor of Engineering - BE, Bachelor of Engineering - BE at University of East LondonHigh School, High School at El Kafrawy Official Language Schools
English, Arabic, French, Greek, German
Stackoverflow
162reputation
45kreached
6answers
6questions
Github Skills (16)
testing10
ivy10
pytorch10
machine-learning10
python10
deeplearning-ai9
deep-learning9
tensorflow8
numpy8
jax8
joptionpane6
http6
html6
javascript6
apache6
Programming languages (9)
Github contributions (5)
ivy-llc/ivy
Dec 2022 - Dec 2022
Convert Machine Learning Code Between Frameworks
Role in this project:
ML Engineer
ML EngineerContributions:142 reviews, 1 commit, 63 PRs in 1 day
Contributions summary:Ziad contributed to the implementation and testing of machine learning loss functions within the Ivy framework, specifically focusing on the Torch frontend. The contributions include adding the huber_loss function, the nonzero function for various backends (Torch, NumPy, Jax), and the hinge_embedding_loss function. Additionally, the user updated and documented hypothesis helpers for array-related testing and fixed testing errors.
pythontensorflowframework-learningtemplatedata-science
ZiadAmerr/ivy
Nov 2022 - Feb 2023
The Unified Machine Learning Framework
Contributions:136 pushes, 32 branches in 3 months
pythoncaffe2data-sciencedeep-learningmachine-learning
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