Yury Kashnitsky
Staff Generative AI Field Solutions Architect
Randstad, Netherlands
Summary
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Rockstar🎓
Top SchoolYury Kashnitsky is a Staff Generative AI Field Solutions Architect at Google Cloud with 11 years of experience applying ML and LLMs to real-world products and business cases. He holds a PhD in applied mathematics and is the leader of the popular open course mlcourse.ai, reflecting a long commitment to hands-on teaching and reproducible ML education. At Elsevier he led teams that turned generative models and NLP into production services—everything from scientific LLMs and RAG pipelines to a library that dramatically increased detection of problematic papers. He combines deep research rigor with pragmatic MLOps practice (MLFlow, DVC, Kubernetes) and a track record of shipping detection, search and classification systems in enterprise settings. A Kaggle Competitions Master and active contributor to the mlcourse.ai repository, he blends competition-grade modeling skills with strong product and stakeholder orientation. Based in the Randstad, he specializes in translating cutting-edge GenAI into measurable business impact across scientific and commercial domains.
11 years of coding experience
14 years of employment as a software developer
Doctor of Philosophy - PhD Applied Mathematics, Doctor of Philosophy - PhD Applied Mathematics at Higher School of EconomicsMaster's degree Applied Mathematics and Computer Science, Master's degree Applied Mathematics and Computer Science at Moscow Institute of Physics and Technology (State University) (MIPT)
English, Dutch, Russian
Stackoverflow
21reputation
0reached
1answer
0questions
Github Skills (14)
data-analysis10
scikit10
jupyter-notebook10
machine-learning10
python10
scikit-learn10
time-series9
pandas9
regression9
algorithms8
data-science8
ipad6
pytorch4
tensorflow4
Programming languages (10)
Github contributions (5)
Yorko/mlcourse.ai
Dec 2021 - Jan 2023
Open Machine Learning Course
Role in this project:
Data Scientist
Data ScientistContributions:1 release, 8 reviews, 112 commits in 1 year 1 month
Contributions summary:Yury primarily contributed to the course content related to machine learning, focusing on correcting typos, fixing broken links, and updating code examples within the Jupyter notebooks. Their work involved modifications to assignments and demonstrations across several topics, including boosting, time series analysis, and regression. They demonstrated their knowledge of data science by updating code and examples. These edits helped improve the learning experience by ensuring the accuracy and functionality of the course materials.
seabornpythonvowpal-wabbitscipydata-science
cs-hse/ML_DM_HSE_minor
Aug 2015 - Dec 2016
Contributions:1 PR, 88 pushes, 1 branch in 1 year 3 months
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