• 👋 Hi, I'm Shunyao Yin (@yinshunyao)
• 📫 Contact: yinshunyao@qq.com

About Me

AI product engineer with hands-on experience in Python full-stack development, AI agent platform engineering, and CV annotation system design.
I focus on turning complex AI workflows into stable, usable products with clear architecture and efficient delivery.

Core Technical Strengths

• Python engineering: Django / FastAPI / Flask / gRPC, API design, service orchestration, and automation tooling
• AI application integration: LLM integration (Qwen), agent execution flow design, tool calling and capability abstraction
• Data & annotation systems: multi-source data ingestion, template-based annotation workflow, 3D annotation scenario support
• CV/ML engineering foundation: PyTorch / TensorFlow / OpenCV / NumPy with product-oriented implementation mindset
• Delivery & maintainability: modular architecture, environment bootstrap scripts, reproducible local deployment, and operation-friendly design

Project Highlights

1) Codiiy - Local AI Automation Assistant Platform

• Designed and implemented a layered architecture: Web UI ↔ Django service ↔ AI agent engine ↔ capability components
• Built practical automation capabilities around local workflows, including file retrieval/operations and messaging notifications
• Integrated LLM (Qwen) into a controllable agent runtime to support conversational task execution
• Improved developer onboarding and reliability with one-command setup/startup flow and standardized runtime conventions

2) AI Annotation Product - Data Access & Annotation Efficiency

• Delivered multi-source data access in one entry point (local upload, HTTP incremental pull, MinIO/SFTP/FTP, etc.)

• Added data preview before source creation to reduce wrong-data ingestion risk and improve data preparation quality

• Enabled intelligent code generation for annotation templates, significantly reducing configuration cost for complex tasks

• Supported 3D point-cloud cuboid annotation workflows, expanding product capability to advanced spatial scenarios

Collaboration Focus

• Open to collaborations on AI products, Web backend systems, and CV data/annotation platforms
• Strong preference for projects that require both engineering depth and product delivery speed