01/2021 - Hiện tại
1. Developed, optimized, and maintained an AI inference service
- Improved the inference throughput by up to 50%.
- Refactored and optimized the AI inference service code using object-oriented programming and design patterns, successfully reducing the codebase from over 4,000 lines to approximately 2,000 lines.
- Developed comprehensive unit tests, achieving an impressive test coverage rate of 93%. These tests played a pivotal role in greatly improving the stability of the code.
2. Developed a monitoring system using Prometheus and Loki to track system resource utilization and AI inference metrics on production servers.
3. Developed an AI model deployment flow using GitLab CI/CD to start inference services on different stage environment servers using Kubernetes.
4. Developed a Kubernetes-in-Kubernetes environment on a development server to simulate the production environment across various factory servers.
5. Optimized, and maintained the Auto-Scheduler API for a web training platform.
6. Developed, optimized, and maintained a defect detection model
- Capacitor component defect detection model with 0% leakage and overkill less than 1%.
- Developed an inference model and implemented the corresponding code for detecting defects in IC components.