Victoriya Vertlib
Full Stack Web Developer at K.S.P Group (P.S.D.S Enterprises Ltd.)
Haifa District, Israel
Summary
🤩
Rockstar🎓
Top SchoolVictoriya Vertlib is a full stack web developer and designer who blends a Technion practical engineering background with formal Fullstack training from John Bryce and nine years of hands-on experience. She currently builds creative, user-focused web solutions at K.S.P, working across JavaScript frameworks (React, Angular, Vue), Node/Express backends, and SQL tooling like Sequelize. Her designer’s eye (Photoshop, Illustrator) lets her deliver polished front-ends while still handling backend performance and integration details. Previously at Intel as a validation technician, she brings disciplined testing and systems thinking to development and QA. An active contributor to open-source ML tooling, she improved regression, SVD, and tSNE implementations in the oneDAL project—demonstrating comfort with numerical algorithms beyond typical web work. That mix of visual design, full-stack engineering, and ML-oriented contributions makes her adept at turning complex data-driven ideas into elegant web experiences.
9 years of coding experience
Practical engineer, Computer Software and Media Applications, Practical engineer, Computer Software and Media Applications at Technion - Israel Institute of TechnologyFullstack Web Developer, Fullstack Web Developer at John Bryce
Github Skills (6)
machine-learning10
oneapi10
cpp10
data-analysis9
ai8
analytics7
Programming languages (3)
Github contributions (5)
uxlfoundation/oneDAL
Mar 2020 - Dec 2022
oneAPI Data Analytics Library (oneDAL)
Role in this project:
ML Engineer
ML EngineerContributions:409 reviews, 10 commits, 124 PRs in 2 years 9 months
Contributions summary:Victoriya contributed to the oneDAL library, focusing on machine learning algorithm implementations and improvements. Their work includes adding and refining training capabilities for linear and ridge regression models, accommodating scenarios with fewer observations than beta coefficients. They also enhanced the SVD implementation, enabling its use with the `svdDense` method when the number of observations is less than the number of features and optimizing various related computations. Furthermore, they removed size restrictions within the documentation and performed performance improvements within the tSNE algorithm.
swrepodata-analyticsanalyticscppdata-analysis
Vika-F/daal
Dec 2019 - Apr 2025
Intel® oneAPI Data Analytics Library (oneDAL)
Contributions:72 PRs, 444 pushes, 138 branches in 5 years 4 months
data-analyticsanalyticsinteloneapianalytics-library
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