Magdalena Anioł
Machine Learning Engineer at Explosion
Huesca, Aragon, Spain
Summary
🤩
Rockstar🎓
Top SchoolMagdalena Anioł is a Machine Learning Engineer with four years of focused experience in NLP and a longer background in language engineering and computational linguistics across companies like Explosion, VERBIO, Intel, and Google. She has led the Prodigy annotation team and contributed full‑stack to its widely used open-source recipes, improving annotation workflows for text classification and NER integrated with spaCy. Based in Huesca, Spain, she combines production ML engineering with practical tooling and annotation expertise, bridging model development and data curation. Her MSc in Speech and Language Processing underpins a pragmatic approach to solving real-world language problems, and her work often surfaces in developer-facing tooling rather than only model papers.
4 years of coding experience
7 years of employment as a software developer
Master of Science (MSc) Speech and Language Processing, Master of Science (MSc) Speech and Language Processing at The University of Edinburgh
Github Skills (13)
annotator10
prodigy10
nlp10
spacy10
python10
text-classification10
natural-language-processing10
annotations10
data-annotation9
machine-learning9
dataannotations9
active-learning8
unit-testing6
Programming languages (4)
Github contributions (5)
explosion/prodigy-recipes
Jan 2022 - Jan 2023
🍳 Recipes for the Prodigy, our fully scriptable annotation tool
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:16 reviews, 40 commits, 16 PRs in 11 months
Contributions summary:Magdalena primarily contributed to the development of annotation recipes within the Prodigy framework, a fully scriptable annotation tool. Their work involved creating and refining recipes for text classification tasks, including textcat.correct, textcat.manual, and ner.fuzzy.manual, showcasing proficiency in integrating spaCy models and implementing custom annotation workflows. They also contributed to testing and utility function improvements, enhancing the tool's functionality and ease of use. Additionally, the user added example data and made formatting and comment additions to make the tool more user-friendly.
nlprecipesactive-learningdata-annotationdata-science
explosion/prodigy-pdf
Oct 2023 - Aug 2025
A Prodigy plugin for PDF annotation
Contributions:6 releases, 8 reviews, 9 PRs in 1 year 10 months
pdf-annotation
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