Євген

Evgeny Nevodnich
TECHNICAL SUPPORT & AUTOMATION ENGINEER

Location: Ukraine | Email: [відкрити контакти](див. вище в блоці «контактна інформація») | Phone: [відкрити контакти](див. вище в блоці «контактна інформація»)

Additional resources:
kaggle.com/evgenynevodnich | github.com/jenyafross | [відкрити контакти](див. вище в блоці «контактна інформація»)

About
Technical support and infrastructure professional with nearly 9 years in
web hosting support and systems administration. Sole owner of the
technical support function at MegaHoster.Network, independently
handling customer issues and improving processes.

Administered 200+ servers and introduced Selenium automation and PHP
API self-service integrations that saved substantial manual work and
reduced support ticket volume. Continuing to develop Python, ML and
LLM skills for practical automation.

Technical Skills:
Languages:
Proficiency: Python
Familiar: SQL, JavaScript, HTML/CSS, C/C++, PHP

MegaHoster.Network Apr 2013 - Feb 2022
Tech Stack
DevOps: NGINX, Apache, PM2, Proxmox (KVM), OpenVPN, Firewall
Configuration, DirectAdmin, ISPmanager, VestaCP, WHMCS.
Backend & Databases: Node.js, Python, PHP | PostgreSQL, MySQL,
MariaDB, MongoDB.
Frontend: JavaScript, React, React Native, Redux, Next.js, HTML5, CSS3,
Bootstrap.

Key Experience & Achievements

Customer Support: Handled customer requests through the WHMCS
ticketing system, troubleshooted issues end-to-end in Ukrainian, Russian
and English. Discussed hardware issues with datacenters staff in English.
Server Administration & Virtualization: Administered 200+ servers, a
portion of which were used for KVM virtualization hosting over 100 client
environments.
Workflow Automation: Implemented automation scripts using Selenium,
created PHP plugins for WHMCS that integrated with datacenter APIs,
allowing users to check server status, reboot, and reinstall operating
systems, reducing support ticket volume and saving up to 16 hours of
manual tasks per week.
Full-Stack Development: Developed and deployed whois service with
geolocation detection from scratch with React.js, Node.js, and MongoDB.
Legacy Refactoring: Rewrote the frontend megahoster.net website using
Bootstrap, ensuring full cross-device responsiveness and improved UI/UX.
Infrastructure Optimization: Configured, supported, and optimized
high-availability web services based on Linux/Nginx/Apache/MySQL/PHP
stacks and managed server virtualization via Proxmox.
Feature Development: Developed custom features and bug fixes using
PHP, JavaScript, and CSS based on client requests.

Freelance Sep 2022 - Present
System administration tasks.

Studying, Self-Education Apr 2021 - Present
Advanced Training: Deepening foundations in mathematics and machine
learning through self-study of research papers, academic literature, and
specialized courses.
Competitive Data Science: Secured 3rd place in the Kaggle Playground
Series (S4E12) and achieved 10th and 11th places in Ukrainian Kaggle
competitions (2024).
Architecture Implementation: Implemented deep learning architectures
from scratch, including GPT-2, Vision Transformers (ViT), and DINO.
Current Focus: Actively exploring Large Language Models (LLMs),
Retrieval-Augmented Generation (RAG), and Multi-Agent systems to solve
complex tasks.

Key ML Projects & Applied Domains
Computer Vision:
Implemented image segmentation models using U-Net architecture and
built image classification pipelines.
Developed object counting systems utilizing YOLO and OpenCV.

Audio & Speech Processing:
Developed sound classification models for insect recognition.
Built an end-to-end Text-to-Speech (TTS) pipeline for an English tutor
application.

Information Retrieval & Search Systems:
Quote Search Pipeline: Collected, processed, and indexed movie subtitles in
Elasticsearch to enable precise quote lookup.
Semantic Movie Search: Built a movie search pipeline. Utilized text
summarization and Late Chunking to generate context-enriched
embeddings from raw subtitles, storing and querying them via
PostgreSQL(pgvector).

Time-Series & Tabular ML:
Built predictive financial models using time-series data from crypto stock
markets.
Solved tabular classification and regression tasks using GBDTs (LightGBM,
CatBoost, XGBoost) and Scikit-Learn.