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tony-gsz/README.md

Hi, I'm Shize Gao, you can call me Tony!

Software Engineering Student @ University of Melbourne
Backend • AWS • Cloud Infrastructure • Full-Stack Systems • AI Pipelines / MLOps

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About Me

I'm a software engineering student at the University of Melbourne with hands-on startup experience building backend systems, cloud infrastructure, and full-stack product workflows.

Most recently, I worked on TinyDOOR at DOOR Global, contributing across backend architecture, Django services, AWS infrastructure, API integration, and end-to-end product delivery for an AI-enabled storytelling platform.

I'm especially interested in building systems that sit at the intersection of:

  • Backend engineering
  • Cloud-native application workflows
  • AI product pipelines
  • Full-stack delivery
  • Production-oriented MLOps / AI systems

Current Focus

  • Building stronger foundations in backend + cloud architecture
  • Moving from full-stack product work toward AI pipelines / MLOps
  • Turning private startup experience into public engineering portfolio demos
  • Creating production-minded systems instead of just prototype projects

Tech Stack

Languages

Python TypeScript JavaScript SQL Java C C++

Frameworks & Tools

Django React Node.js REST APIs Git GitHub Docker PostgreSQL

Cloud / Infra

AWS S3 Lambda Elastic Beanstalk RDS Cognito Amplify CloudFront

AI / Data

PyTorch TensorFlow Keras NumPy Pandas SpaCy


Featured Work

🔹 TinyDOOR System Architecture (Sanitized Case Study)

A public architecture-focused portfolio repo based on my work on TinyDOOR — an AI-enabled storytelling platform.
Focus: backend workflows, cloud infrastructure, request lifecycle design, and async AI product orchestration.

🔹 Async AI Request Pipeline Demo

A minimal public backend demo that simulates a common AI product pattern:
create request → async processing → status polling → result delivery.

🔹 S3 Presigned Upload Demo

A cloud pattern demo showing how to support secure direct client uploads using AWS S3 presigned URLs, similar to real media-heavy product workflows.

🔹 Mixed Reality Gesture Control

A technical project focused on gesture recognition, real-time interaction systems, and smart-home control in mixed reality using Unity and Meta XR tools.

🔹 IoT Infant Scale (Firmware Team Lead)

A systems project combining embedded development, secure device communication, and team coordination in a large-scale engineering capstone.


What I Want to Build

I'm most excited by roles and projects involving:

  • Backend Engineering
  • Cloud Infrastructure
  • Full-Stack Product Systems
  • AI Tooling / AI Product Engineering
  • AI Pipelines / MLOps
  • Production AI Workflows

Portfolio Direction

Most production work I've contributed to is private, so this GitHub is intentionally focused on:

  • Sanitized architecture case studies
  • Public mini-demos of real engineering patterns
  • Backend / cloud / async workflow examples
  • Project writeups that reflect production thinking

Open To

I'm currently open to:

  • Software Engineering Internships
  • Backend / Full-Stack Internships
  • Cloud / Platform Engineering Internships
  • AI Systems / AI Product / MLOps-adjacent opportunities

📍 Based in Melbourne, Australia

Pinned Loading

  1. tinydoor-system-architecture tinydoor-system-architecture Public

    Sanitized architecture case study of a hybrid AI story-generation platform built with Next.js, Django, AWS Lambda, and S3-based async workflows.

  2. Regex-Pattern-Operation Regex-Pattern-Operation Public

    Rhombus AI Web Application for Regex Pattern Matching and Replacement (Django + React + LLM + AWS)

    Python

  3. tony-gsz tony-gsz Public