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  • Singapore

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Achievement: QuickdrawAchievement: Pull Sharkx3Achievement: StarstruckAchievement: YOLOAchievement: Arctic Code Vault Contributor

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zhu-weijie/README.md

Hi there, I'm Zhu Weijie 👋



I'm a Senior Software Engineer based in Singapore with over a decade of experience architecting and developing robust, scalable, and high-performance software solutions.

My core expertise lies in Python and C++ for backend systems, API development, and full-stack applications. I'm passionate about leveraging modern technologies and best practices – including microservices, cloud platforms (AWS/GCP), Docker, Kubernetes, CI/CD, and Agile methodologies – to solve complex problems and deliver impactful products.

I particularly enjoy working on data-intensive applications and systems that support AI/ML workflows.

🚀 Key Projects & Explorations

Here are a few projects that showcase my skills and interests:

  • Alpha-Dash: Full-Stack Financial Data & Portfolio Platform

    • An end-to-end web application built with Python (FastAPI), React/TypeScript, PostgreSQL, Redis, and Celery. Features data integration from financial APIs, portfolio valuation, background data refresh tasks, and CI/CD with GitHub Actions. Demonstrates full-stack development, system architecture, and DevOps practices.

  • Infer-Net: Dockerized Image Classification API & MLOps Demo

    • A machine learning application serving an image classification model (TensorFlow/Keras) via a Python (FastAPI) RESTful API, containerized with Docker. Highlights experience with ML model deployment, API development for inference, and MLOps principles.

🛠️ My Tech Stack & Expertise Includes

  • Languages: Python (Expert), C++ (Proficient), JavaScript/TypeScript, SQL, Go (Familiarity)
  • Backend Frameworks: FastAPI, Django, Flask
  • Frontend: React
  • Databases: PostgreSQL, MySQL, Redis, Neo4j
  • Cloud & DevOps: AWS, GCP, Docker, Docker Compose, Kubernetes (conceptual & practical experience), CI/CD (GitHub Actions, Jenkins), Terraform (basics)
  • AI/ML: Platform development for ML model deployment (Gongga-box), MLOps concepts, TensorFlow/Keras (hands-on model building/serving).
  • Architecture: Microservices, Distributed Systems, RESTful APIs, Event-Driven Architecture, SOLID, OOP.

📫 Let's Connect!

I'm always open to discussing new technologies, interesting projects, or potential collaborations. Feel free to reach out!

Top Langs

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  1. alpha-dash alpha-dash Public

    🧮A full-stack financial portfolio tracker and analyzer, demonstrating advanced backend services, data integration, and dynamic frontend visualization.

    Python

  2. ficc-pricer-stream ficc-pricer-stream Public

    🧮A simulated real-time FICC pricing pipeline built with Python, Docker, and Redis to demonstrate a distributed microservice architecture.

    Python

  3. infer-net infer-net Public

    🧮Production-style, end-to-end Machine Learning API for image classification using FastAPI, Docker, and a full CI/CD pipeline.

    Python

  4. llm-tool-harness llm-tool-harness Public

    🧮A Python library to easily build LLM agents with tool-using capabilities, allowing them to interact with external systems and perform actions.

    Python

  5. langgraph-autopilot langgraph-autopilot Public

    🧮An autonomous software engineering agent that reads GitHub issues, analyzes codebases, and writes and submits code changes to resolve them.

    Python

  6. creator-pulse creator-pulse Public

    🧮An end-to-end MLOps project for real-time YouTube sentiment analysis. Powers a Chrome Extension via a Flask API, deployed on AWS with full CI/CD.

    Python