Full-Stack Developer | Python & ML APIs | AI-Accelerated Workflows
Full-stack developer with 3+ years of experience building production applications using Python (FastAPI), TypeScript, and modern databases. Strong problem-solver who rapidly learns new technologies through AI-assisted development workflows and takes ownership of complex technical challenges.
Backend & APIs: Python (FastAPI), RESTful API design, OAuth2/JWT authentication Databases: PostgreSQL, Firebase, Supabase, IndexedDB Frontend: TypeScript, Next.js, React, Vue.js, Flutter (iOS/Android/Web) AI/ML: YOLO model deployment, ML inference APIs, computer vision pipelines, RAG systems DevOps: Docker, Git, cloud deployment (Render, Vercel, GCP, Digital Ocean) AI-Assisted Development: Claude Code & Cursor - expert in rapid prototyping and AI-accelerated workflows
RESTful API for managing YOLO models with real-time image/video inference, frame extraction, and GIF generation. Deployed on Render with Docker.
- Tech: Python, FastAPI, YOLO, Docker
- Live Demo
Automatic post tracking with dual storage, full-text search, and masonry grid layout.
- Tech: TypeScript, React 19, IndexedDB, Manifest V3
Data pipeline for processing annotated images from Roboflow datasets with intelligent image splitting and automatic bounding box translation.
- Tech: Python, PIL, Shapely, Matplotlib
An inventory system transforming 900+ column Excel file into normalized relational database with AG-Grid Enterprise interface, with features like data comparison when bulk updating, orders file export, labels(serial) management for order batches, one-click price lookup in the order grid, etc.
- Tech: Next.js, TypeScript, PostgreSQL, Supabase
- Demo
Multi-platform (iOS/Android/Web) auction system with live bidding, 37,000+ car database, and video streaming (8x performance improvement via Tencent VOD integration).
- Tech: Flutter, Firebase, Tencent VOD
- Currently in beta testing
- Local LMM assistant with RAG, TTS & Obsidian vault integration
- Expanding expertise in distributed systems and RAG architectures
Russian (Native) | English (Fluent) | Chinese (Fluent)


