Данило

DANYLO KHOMYSHYN
ML ENGINEER

PROFILE
ML Engineering student at Lviv Polytechnic National University (Artificial
Intelligence Systems). I build backend systems and AI pipelines — from RAG and
LLM integrations to REST APIs and vector databases. I focus on writing clean,
production-ready code and want to grow inside a strong engineering team.
CONTACT
[открыть контакты](см. выше в блоке «контактная информация») PROJECTS EXPERIENCE
[открыть контакты](см. выше в блоке «контактная информация») PolyAI Mentor — AI Mentorship Platform — www.polyaimentor.space
github.com/DanyloShi Pet project / Commercial
▸ Designed and built a production-ready backend using Python, FastAPI, PostgreSQL, Redis,
telegram.org/khomyshyn13 and Weaviate.
▸ Developed an end-to-end RAG pipeline for PDF, DOCX, PPTX, and TXT documents:
parsing, chunking, embeddings, semantic retrieval, and LLM response generation.
SKILLS ▸ Implemented asynchronous document indexing with Redis queues, retries, worker
heartbeats, and configurable per-model quotas.
▸ Integrated local and cloud LLMs through Ollama and OpenAI-compatible APIs.
Python (OOP, algorithms, data
▸ Built secure authentication and authorization using JWT, Google OAuth 2.0, guest
structures) sessions, and role-based access control.
RAG pipelines, LLM integration ▸ Containerized the platform with Docker Compose and managed database migrations
PyTorch, TensorFlow, Scikit-learn using SQLAlchemy and Alembic.
Pandas, NumPy, Matplotlib, EasyTrip — Tourist Route Optimization
Seaborn
Research / Pet project
SQL, NoSQL and vector databses ▸ Built a route optimization system using Reinforcement Learning
(MySQL, PostgreSQL, MongoDB, ▸ Applied Deep Q-Network (DQN) — designed environment, reward function, and training
Weavite) loop
▸ Model learns user preferences from interaction history and adjusts route
Docker
recommendations
Git, GitHub ▸ Stack: Python, PyTorch, NumPy
Django, FastAPI, Flask
Working with APIs (OpenAI, Real Estate Price Prediction
Google, Telegram) Research / Pet project
▸ Ensemble model comparison: Random Forest, XGBoostRegressor, CatBoostRegressor,
Basic Linux, CLI
MLPRegressor
▸ Feature engineering, cross-validation, bias-variance analysis
▸ Stack: Python, Scikit-learn, XGBoost, CatBoost, Pandas, Matplotlib
LANGUAGES
2D Game Engine (PyGame)
Ukrainian (Fluent) Pet project
English (B2 FCE certificated) ▸ Created 2D game using PyGame
▸ Implemented game logic, physics, and rendering loop

C E R T I F I CAT E S EDUCATION
Participation on Data
Lviv Academic Gymnasium 2016-2023
Science Bootcamp
Since I studied at a gymnasium with a math focus, I really liked math
Linux basics from and participated in math olympiads, which helped me pass the NMT
Prometheus with the best score.
B2 First (Cambridge
IT-Step Academy 2016-2021
Assessment English)
I studied various areas of IT such as web programming,
computer application development, games, robotics. I have
taught Python, C++, Java, HTML, CSS, JavaScript.

Lviv Polytechnic National University 2023-present
Institute of Computer Sciences and Information Technologies
“Artificial Intelligence Systems ” program