Mateusz Klimaszewski
Member Of Technical Staff at Cohere
Warsaw, Masovian Voivodeship, Poland
Summary
👤
Senior🎓
Top SchoolMateusz Klimaszewski is a PhD-trained NLP and ML engineer with a decade of experience building research-driven language technologies across academia and industry. He has combined deep research roles at Warsaw University of Technology and the University of Edinburgh with applied engineering at companies like Cohere, Aveni (FinLLM), Booking.com and Google, spanning NMT, modular LLMs and production ML systems. An active open-source contributor, he has improved core training and evaluation flows in the widely used AllenNLP library, reflecting hands-on expertise in model training and reproducible research. Mateusz is currently a Member of Technical Staff at Cohere and remains open to research internships in NLP/IE/ML, bringing both theoretical rigor and product-oriented delivery. He blends classical software engineering (Java, Scala, Spark) with state-of-the-art deep learning (PyTorch, Transformer-based LLMs), and has a track record of moving models from experimental code to deployed pipelines. Colleagues value his ability to navigate both complex research questions and practical engineering constraints, particularly in multilingual and finance-focused LLM projects.
10 years of coding experience
6 years of employment as a software developer
Computer Science, Computer Science at University of ViennaDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Warsaw University of Technology
Github Skills (5)
pytorch10
nlp10
deep-learning10
python10
data-science9
Programming languages (5)
Github contributions (5)
allenai/allennlp
Apr 2020 - Oct 2020
An open-source NLP research library, built on PyTorch.
Role in this project:
ML Engineer
ML EngineerContributions:5 commits, 7 PRs, 10 comments in 6 months
Contributions summary:Mateusz made several contributions related to the AllenNLP library, focusing on improvements and fixes related to the training process and core functionality. The commits included adding features for logging regularization loss, updating the validation process, and fixing URL formatting in documentation. These changes demonstrate involvement in model training and evaluation within the NLP research library.
nlppytorchtransformerspythonbert
ipipan/combo
Feb 2020 - Nov 2020
Contributions:45 commits, 18 pushes, 2 comments in 9 months
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