Professional Overview
Machine learning engineer with a professional focus on LLM systems, agents, and RAG. I build generative pipelines, integrate models into services, and design systems with transparent, auditable decision logic. I have full-cycle experience: from data preparation and model training to Docker deployment, monitoring, and testing. AI Master's student at
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built an AI agent that monitors therapy for children with rheumatic diseases
- Designed and implemented an end-to-end pipeline for processing medical messages
- Built a RAG system over 47 clinical PDFs with pgvector retrieval
- Implemented human-in-the-loop review (clinician approves, edits ,regects)
- Engineered for scale: new diagnoses are added via YAML with no code changes
Education
Field of Study: Software Engineering
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
