Kadar Akos
Machine Learning Engineer at AIVA Technologies
Summary
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RockstarKadar Akos is a Machine Learning Engineer with 11 years of experience specializing in NLP and music-related ML projects. He contributes to high-profile open-source libraries like spaCy and Thinc, where he implemented and tested new activation functions, integrated them into trainable layers, and improved testing infrastructure and robustness. His work demonstrates a strong focus on correctness and compatibility—validating implementations against PyTorch and adding features like label smoothing to core loss functions. Comfortable across engineering and QA roles, he bridges research-quality model work with production-grade testing and automation. Colleagues can expect a pragmatic engineer who cares as much about reliable pipelines and test coverage as about model innovations.
11 years of coding experience
Github Skills (18)
pytorch10
debug10
artificial-intelligence10
pytest10
python10
testing10
machine-learning10
deep-learning10
spacy10
ai10
numpy9
natural-language-processing9
functional-programming9
nlp9
type-checking8
Programming languages (8)
Github contributions (5)
explosion/thinc
Jan 2022 - Oct 2022
🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
Role in this project:
ML Engineer
ML EngineerContributions:122 reviews, 16 commits, 21 PRs in 9 months
Contributions summary:Kadar significantly contributed to the implementation and testing of new activation functions within the `thinc` library, a functional deep learning framework. Their work included adding hard-sigmoid, ReLU, swish, and GELU activations, along with their corresponding forward and backward propagation operations. Furthermore, the user integrated these new functions into trainable dense layers and performed extensive testing against PyTorch implementations, ensuring compatibility and correctness. They also added label smoothing to categorical cross-entropy.
pythonfunctional-programmingtensorflowtype-checkingnatural-language-processing
explosion/spaCy
Feb 2022 - Dec 2022
💫 Industrial-strength Natural Language Processing (NLP) in Python
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:72 reviews, 20 commits, 20 PRs in 10 months
Contributions summary:Kadar primarily focused on improving the testing infrastructure and addressing bugs within the spaCy library. Their commits involved creating and refining tests for various components like the NER, parser, and text categorization modules. The contributions included fixing argument orders, adding new test cases, and enhancing error messages, indicating a strong emphasis on code quality and robustness. They also made several changes to the tests by introducing new labels and applying them for testing.
fairness-mlpythondata-preprocessinglanguage-processingtokenization
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