Alexander Makaryev
Senior Software Developer at Intel Corporation
Nizhniy Novgorod, Nizhniy Novgorod, Russia
Summary
🤩
Rockstar🎓
Top SchoolAlexander Makaryev is a Senior Software Developer with 7+ years of professional experience, currently building software at Intel from Nizhniy Novgorod. He combines a strong applied mathematics background (MSc/BSc) with hands-on engineering across backend systems and data-science tooling, contributing to high-profile open-source projects such as Numba and performance extensions for scikit-learn. His contributions span code improvements, test refactors, and practical examples that bridge ML libraries with Intel oneAPI DAAL, reflecting both low-level compiler-aware work and applied ML acceleration. Previously he advanced software delivery at SPSR-Express and Incotex Electronics Group, showing a steady progression from developer to senior roles. Colleagues would note his attention to code quality and tests, plus a habit of improving documentation and examples that make complex tools easier to adopt.
7 years of coding experience
8 years of employment as a software developer
Master's degree, Applied Mathematics and Informatics, Master's degree, Applied Mathematics and Informatics at Нижегородский Государственный Университет им. Н.И. Лобачевского (ННГУ)
Github Skills (14)
scikit10
scikit-learn10
compiler10
machine-learning10
machine-learning-algorithms10
compiler-compiler10
numba10
python10
numpy10
data-analysis10
testing9
llvm9
dbscan9
documentation8
Programming languages (4)
Github contributions (5)
uxlfoundation/scikit-learn-intelex
Sep 2018 - Jul 2020
Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
Role in this project:
Data Scientist
Data ScientistContributions:2 releases, 2 reviews, 120 commits in 1 year 10 months
Contributions summary:Alexander focused on enhancing the examples within the repository to demonstrate the usage of Intel's oneAPI Data Analytics Library (DAAL) for Scikit-learn. Contributions include adding examples for various machine learning algorithms such as Lasso Regression, Elastic Net, and DBSCAN. The changes show a focus on incorporating different prediction options, and generating outputs for a variety of algorithms.
pythonswrepoai-machine-learningdata-scienceintel
numba/numba
Feb 2021 - Mar 2021
NumPy aware dynamic Python compiler using LLVM
Role in this project:Backend Developer
Backend DeveloperContributions:3 reviews, 6 commits, 6 PRs in 21 days
Contributions summary:Alexander primarily contributed to the `numba/numba` repository by fixing typos in documentation and improving the codebase. Their work included checking for internal types in array expression rewrites and using `textwrap.dedent`. The user also refactored and moved the `create_temp_module` function into `numba.tests.support`. Further changes were made to the test suite and to `array_exprs.py` to improve array expression handling.
cudapythonparallelnumpynumba
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