Oleksii

OLEXII SEREBRYANSKY
JUNIOR AI ENGINEER

[відкрити контакти](див. вище в блоці «контактна інформація») Plzen, CZ
Oleksii Serebrianskyi [відкрити контакти](див. вище в блоці «контактна інформація»)

PROFESSIONAL SUMMARY
I am a Python Developer transitioning into AI Engineering, focusing on RAG, semantic search,
embeddings and vector-based information retrieval.

I have hands-on experience with Python applications and ML projects, including:

- PyTorch and neural network architectures.
- Data processing and preprocessing.
- Embeddings and semantic similarity.
- Automated data collection, web scraping and browser automation.
- PostgreSQL, SQLAlchemy and backend development.
- Computer Vision with YOLOv8, OpenCV and MobileNetV3.

Currently, I am deepening my knowledge of RAG architectures, vector databases, document retrieval
and LLM-powered applications, with a focus on building practical AI solutions.

TECHNICAL SKILLS
CAI Engineering & Machine Learning Deep Learning
Embedding Models PyTorch
NLP MobileNetV3
RAG Convolutional Neural Networks
Web Scraping & Browser Automation Model Training and Evaluation
Vector Search GPU-based Training / CUDA

Development Tools
Programming
Git / GitHub
Python
Linux / Ubuntu
NumPy
Google Colab
Pandas
SQLAlchemy
SQL
PostgreSQL
REST API Integration

EDUCATION
Automotive / Motorsport Hillel IT School
Engineering Machine Learning Engineer
Odesa National Polytechnic Graduated: 2026
University (ONPU) Python Base
Graduated: 2024 Graduated: 2025

PROFESSIONAL EXPERIENCE
Grant Matching & Embedding Model
Machine Learning / NLP
GitHub: https://github.com/AlexeySerebryansky/Grant_cheker_bot

Developing an embedding-based machine learning solution for semantic grant matching.
Designed structured grant data representations.
Developed automated data collection.
Prepared datasets for model training.
Worked with textual preprocessing.
Explored vector representations and semantic similarity.
Used PyTorch and Google Colab for experimentation.
Technologies: Python, PyTorch, Pandas, Google Colab.

BidFax Parser
Python / Data Engineering
GitHub: https://github.com/AlexeySerebryansky/BidFax_parser

Developed a multi-stage web scraping system.
Implemented parallel data processing.
Integrated PostgreSQL using SQLAlchemy.
Built reusable parsing components.
Implemented error handling and data validation.
Technologies: Python, BeautifulSoup, SQLAlchemy, PostgreSQL.

DP Document Bot
Browser Automation / Web Scraping / Python Automation
GitHub: https://github.com/AlexeySerebryansky/DP_Document_bot

Developed an automated monitoring application for tracking appointment availability on web
resources.
Implemented automated browser-based monitoring.
Used anti-detect browser technology for interacting with web resources.
Automated availability checks and data collection.
Integrated monitoring results with Telegram notifications.
Implemented background execution and continuous monitoring.
Configured deployment and persistent operation on Linux servers.
Used SQLite for data persistence.
Technologies: Python, Anti-detect Browsers, Browser Automation, Web Scraping, Aiogram, SQLite,
Linux, systemd.

Poker Analytics Assistant
Computer Vision / Deep Learning
GitHub: https://github.com/AlexeySerebryansky/Poker_Analytic

Developed a computer vision application for automated recognition of playing cards in poker table
images.
Implemented object detection using YOLOv8.
Developed a 52-class playing card classification model using MobileNetV3-Small.
Integrated PyTorch models with OpenCV image processing.
Built a real-time processing pipeline.
Developed a desktop interface using PyQt6.
Integrated visual recognition with poker probability calculations.
Technologies: Python, PyTorch, YOLOv8, MobileNetV3, OpenCV, NumPy, PyQt6.