Karol Lasocki
Senior Machine Learning Engineer at BottleCap AI
Czechia
Summary
👤
Senior🎓
Top SchoolKarol Lasocki is a Senior Machine Learning Engineer with 8 years of experience building production ML systems across NLP, TTS and LLM training pipelines. He has driven measurable product impact at JetBrains—tripling autocompletion acceptance with a low-latency filter—and contributed to open-source NLP tooling like Flair, improving sequence tagging, metrics and model interpretability. His work spans research and engineering: from state-of-the-art melody-conditioned generation in academia to scalable multilingual TTS at Amazon and efficiency-focused LLM training at BottleCap AI. Comfortable across backend, model, and metric design, he combines hands-on implementation with UX-informed evaluation and team mentorship. Based in Czechia, he brings a multidisciplinary curiosity—cognitive science, VR and language learning—that often influences creative ML solutions.
8 years of coding experience
4 years of employment as a software developer
AGH UniversityMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at SECCLO Master's Programme in Security and Cloud Computing (Erasmus Mundus)SECCLO Master's Programme in Security and Cloud Computing, Computer Science, SECCLO Master's Programme in Security and Cloud Computing, Computer Science at Aalto UniversityMaster's degree, Computer Science, Master's degree, Computer Science at University of Eastern FinlandNorwegian University of Science and Technology
English, Japanese, German, Polish, Spanish, Czech
Stackoverflow
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Github Skills (10)
sequence-labeling10
pytorch10
machine-learning10
nlp10
python10
text-classification10
natural-language-processing9
word-embeddings9
architecture8
architectures8
Programming languages (9)
Github contributions (5)
flairNLP/flair
Aug 2019 - Jan 2020
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Role in this project:
ML Engineer
ML EngineerContributions:6 commits, 2 PRs, 2 comments in 5 months
Contributions summary:Karol significantly contributed to the FlairNLP project by adding and refining features related to sequence tagging and text classification models. They implemented F-beta score calculations and integrated them as a key evaluation metric. Further contributions include adding class weights to loss functions and enhancing the model's logging for new parameters, ultimately improving the functionality and interpretability of the models. Minor refactoring was also carried out.
nlppytorchnamed-entity-recognitionartsemantic-role-labeling
klasocki/operating-systems
Mar 2019 - Jun 2019
Contributions:33 commits, 14 pushes, 1 branch in 2 months
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