Alexander Myltsev
Machine Learning Engineer And Researcher (Remote Contractor) at LAMBDA HSE
Moscow, Moscow, Russia
Summary
👤
Senior🎓
Top SchoolAlexander Myltsev is a Machine Learning Engineer and Researcher with 17 years of experience building high-performance backend systems, data pipelines and ML solutions across finance, biodiversity, and manufacturing. He combines a strong functional-programming background and systems engineering skills—evident from contributions to CatBoost and the parboiled2 PEG parser—with hands-on work in Scala, Python, and distributed deployments. Alexander has a track record of turning research into production: speeding scientific-name parsing by 100x, cutting library indexing from weeks to hours, and applying ML to reduce costs in process manufacturing. He also designed investor-facing portfolio analysis tooling and open-sourced core libraries, showing an unusual blend of quantitative finance acumen and pragmatic engineering. Based in Moscow, he pairs academic rigor from MIPT with extensive open-source collaboration and a knack for performance-driven refactoring.
17 years of coding experience
4 years of employment as a software developer
Master of Science (M.Sc.), Mathematics (Computer Science), 5.0/5.0, Master of Science (M.Sc.), Mathematics (Computer Science), 5.0/5.0 at Moscow Institute of Physics and Technology (State University) (MIPT)Diplomated Specialist (Computing Systems and Networks), Faculty of Electronics: Department of Computing Systems and Network, 4.5/5.0, Diplomated Specialist (Computing Systems and Networks), Faculty of Electronics: Department of Computing Systems and Network, 4.5/5.0 at South Ural State University (SUSU)Completed 1st year courses, Completed 1st year courses at Yandex School of Data Analysis
Russian, English
Stackoverflow
469reputation
24kreached
6answers
17questions
Github Skills (23)
catboost10
c-language10
fileio10
file-processing10
file-handling10
file-access10
cprogramming-language10
unit-testing9
system-design8
data-structures6
vagrant6
median6
entity-framework6
sbt6
python6
Programming languages (13)
Github contributions (5)
catboost/catboost
May 2018 - Jan 2023
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Role in this project:
Back-end Developer & System Engineer
Back-end Developer & System EngineerContributions:19 commits in 4 years 8 months
Contributions summary:Alexander contributed to the `catboost` project by addressing core system-level issues and improving code quality. Their work included fixing typos, refactoring and optimizing file I/O operations, and adding unit tests for file-related functionalities like pipe reading. Furthermore, the user worked on refactoring and restructuring existing code by moving code between directories, updating file references, and adding comments to document existing code. These modifications indicate a focus on maintainability and system performance.
kagglexgboostpythondata-mininglightgbm
hse-cs-ami/yabloko-public
Jan 2023 - Jan 2025
Contributions:2 PRs, 37 pushes, 7 branches in 2 years
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