Jie-Ying (Peter) Li
Software Engineer, Open Source Contributor
About
2 years of experience in software engineering, specializing in AI, data science, and backend development. Proficient in Python, C++, and various machine learning frameworks. Strong background in computer vision and data engineering. Proven ability to develop and optimize machine learning algorithms for real-world applications. Excellent problem-solving skills and a passion for continuous learning.
Skills
ML/DL
Model Deployment
Model Optimization
Data Engineering
Backend Development
Work Experience
TrendMicro
2025.02 - Present
AI/ML Engineer
Developed and optimized machine learning algorithms for cybersecurity applications.
Python
C++
HuggingFace
PyTorch
ONNX
GCP
Vertex AI
OmniEyes
2024.02 - 2025.02
AI Algorithm Engineer
Developed Advanced Driver Assistance Systems (ADAS) and CRM systems.
Python
Kotlin
TensorFlow
OpenCV
PostgreSQL
MongoDB
Serverless
AWS
Docker
Education
National Tsing Hua University
2021 - 2023
Master's Degree in Information Systems and Applications, GPA: 4.23/4.30
Yuan Ze University
2017 - 2021
Bachelor's Degree in Computer Science and Engineering, GPA: 3.79/4.00
Extra Curricular & Certifications
Completed the Back-End Engineering job simulation, taking over development of an unfinished project for the Lyft Rentals team. Drafted a UML class diagram representing a new reorganized architecture. Refactored a messy codebase inherited from another team to accurately reflect my new design. Implemented unit tests and added new functionality using test-driven development.
Completed a job simulation that involved building containers for one of Ford's backend development teams. Developed a backend to stream engine temperature sensor readings from cars to mobile phones. Connected a Flask server to a Redis instance using Docker Compose.
Designed and simple and scalable hosting architecture based on Elastic Beanstalk for a client experiencing significant growth and slow response times. Described my proposed architecture in plain language ensuring my client understood how it works and how costs will be calculated for it.
Projects
Efficient Hand Gesture Recognition using Multi Task Multi Modal Learning and Self Distillation
github.competer0512lee/Efficient-Hand-Gesture-Recognition-using-Multi-Task-Multi-Modal-Learning-and-Self-Distillation
PyTorch implementation of the thesis project.
PyTorch
OpenCV
MIT 6.824 Distributed Systems
github.competer0512lee/MIT6.824-Distributed-Systems
The labs from MIT6.824-Distributed-Systems
Go
Distrubuted System
Shopping Cart System
github.competer0512lee/shopping-cart-system-go
A simple e-commerce shopping cart system built with Go (backend) and React (frontend), featuring real-time cart updates and a responsive design.
Go
Gin
MongoDB
Docker