Vladyslav

Vladyslav Hromovyi Email: [відкрити контакти](див. вище в блоці «контактна інформація»)
Telegram: @Ezplosive
Junior Machine Learning Engineer / NLP / LLM
Location: Rivne, Ukraine
GitHub: ExplosiveDev

PROFILE
I am a 3rd-year Software Engineering student with 2.5 year of professional experience as an ML Software Engineer and Classic
ML Engineer. My background combines Full-Stack development (.NET, React, SignalR) with a deep expertise in building end-to-end
ML pipelines - from intelligent data collection and preprocessing to deploying RAG systems and transformer-based models.

EXPERIENCE
E-signature platform Python, FastAPI, RAG, MInference
ML Software Engineer Jan 2025 - Dec 2025
• Architected a scalable REST API using FastAPI with Dependency Injection patterns and strict data validation through Pydantic
• Implemented a Hybrid Search architecture in Elasticsearch, combining vector embeddings with structured metadata for deter-
ministic filtering
• Optimized document processing by implementing a recursive chunking strategy with overlap, significantly improving context
retrieval quality for semantic search
• Used MInference to optimize the calculation of attention matrices in documents with long context, which resulted in reduced
memory consumption and latency.

UKRSIBTECH (Outstaff Project) Python, XGBoost, Random Fores, Scikit-learn, SMOTE
Classic ML Engineer July 2023 - Nov 2024
• Implemented a fraud detection system (Anti-Fraud), achieving a high Precision indicator with a low proportion of the target class
(Imbalanced Classes)
• Automating the analysis of customer sentiment in social networks and chats, achieving a high F1-score
• Developed a full lifecycle of ML models to prepare data for deployment, which reduced the time to release updates

Internet Messenger .NET Core, React, SignalR, PostgreSQL
Full-Stack Developer (pet project) Feb 2022 - Apr 2022
• Developed REST APIs using ASP.NET Core and designed database schemas for CRUD operations.
• Implemented real-time messaging, chat features, and user statuses using SignalR.
• Managed application state with Redux Toolkit and local data storage with IndexedDB.

TECHNICAL SKILLS
• Languages: Python , C#
• Classic ML: Classification, regression, clustering, XGBoost, Random Forest, Exploratory Data Analysis (EDA), Feature engineering
• NLP/LLM: Transformers, RAG-systems, Embeddings (Word2Vec, TF-IDF), RNN/LSTM, Hugging Face
• Data/Stores: PostgreSQL, Qdrant, Redis, SQLite
• Frameworks/Tools: FastAPI, Pydantic, ASP.NET Core, React, Docker, Pandas, Scikit-learn

EDUCATION
National University of Water and Environmental Engineering Rivne, Ukraine
B.Sc. in Software Engineering Aug 2022 – Dec 2027 (Expected)

LANGUAGES
• Ukraine: Native
• English: B1

SOFT SKILLS
• Clear communication, problem solving, collaboration, adaptability, initiative

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