Анастасія

Anastasiia Kharchenko
AI Engineer
CONTACT
Phone
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Email
[открыть контакты](см. выше в блоке «контактная информация»)
Telegram
@Kharchenko_Anastasia
GitHub
KharchenkoAnastasia
Scopus ID
57211625706
SKILLS
AI & LLM
• Prompt Engineering
• RAG architecture
• OpenAI API, Whisper
• LLM Evaluation
• Embeddings & Vector Search
Programming
• Python
• SQL / PostgreSQL
ML & Data
• Scikit-Learn, TensorFlow
• Pandas, NumPy
Tools
• Docker
• GitHub Actions
• Label Studio
• Pytest, Mypy, Ruff

CERTIFICATION
TensorFlow Developer Certificate
Sep 2024 – Jan 2027
EDUCATION
ML Zoomcamp
DataTalks.Club
Sep 2024 – Jan 2025
Mentoring Program
Vona Tech Community
Jun – Sep 2024
ML Bootcamp Ukraine
Google
Jul – Sep 2023
Master | Bachelor
Software Engineering
Zaporizhzhia Polytechnic
2016 – 2022
SUMMARY
AI Engineer with hands-on experience in building LLM-based applications, including RAG systems and prompt-driven workflows using OpenAI APIs. Focused on designing structured prompts, improving AI output quality, and building reliable, context-aware assistants. Experienced in prompt iteration, evaluation strategies, and multi-step AI interactions. Strong background in Python, machine learning, and data processing, with a focus on applying AI to real-world use cases and automation scenarios.
WORK EXPERIENCE
Python AI Internship - Meduzzen
Dec 2025 – Feb 2026
• Developed AI assistant with RAG architecture using OpenAI APIs
• Integrated embeddings and vector search for context-aware responses
• Implemented audio transcription via OpenAI Whisper API, automatically indexing content for semantic search
• Implemented tool-calling, async processing, and structured prompt design
• Improved response quality through similarity thresholds and fallback strategies
Content Analyst - Jiji
Mar 2022 – Dec 2025
• Developed an AI-powered moderation assistant to automatically classify listings and identify prohibited content using LLMs (OpenAI API), vector databases, and semantic search, significantly reducing manual moderation time
• Collected, structured, and analyzed user behavior data to identify trends, anomalies, and potential risks
• Prepared analytical reports to support moderation decisions and improve platform safety
Data Science Intern - Lemberg Solutions
Jul – Oct 2023
• Processed and analyzed sensor data (accelerometer, gyroscope): artifact removal, normalization, and signal filtering
• Built and labeled a high-frequency dataset and developed ML models (accuracy up to 0.85)
• Compared feature-selection methods and evaluated performance metrics
PERSONAL PROJECT
Ship Segmentation (Kaggle Airbus Ship Detection Challenge)
Developed a U-Net based deep learning model to perform binary segmentation of ships in satellite images.
Tech stack: TensorFlow, Scikit-Learn, NumPy, Docker, GitHub Actions
GitHub: Airbus-Ship-Detection
ACHIEVEMENTS
5 scientific publications in Scopus, h-index=5
3rd place in the All-Ukrainian competition of student scientific works in the specialty "Computer Science" 2020/2021 for the research paper "Modified genetic algorithm to determine the location of the distribution power supply networks in the city"