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Michael Hoon

  • 24 years old
  • Made in Singapore ๐Ÿ‡ธ๐Ÿ‡ฌ
  • AI/Data Engineer
  • Singapore University of Technology and Design
  • Resume/CV

About me

Hi ๐Ÿ‘‹, Iโ€™m

Typing SVG


I study Systems Engineering (Business Analytics, minor in AI), and build systems where research meets production. Iโ€™m fascinated by tech for public good and enjoy turning complex problems into reliable tools. Lately, thatโ€™s meant working on multi-agent LLM systems and learning how to make data workflows scalable and resilient in the cloud (AWS).

My current focus is on data engineering and cloud infrastructure: Iโ€™m building pipelines that reliably move and transform data, experimenting with orchestration patterns, and deploying models so theyโ€™re useful outside notebooks.

Outside of code, I capture the world through photography, recharge on hikes, run for clarity, and travel to learn new perspectives. Someday I plan to adopt a cat ๐Ÿฑ!


๐Ÿ”ฅ Actively seeking full-time roles in Data or AI Engineering for May 2026 openings!

Work Experience

Jun. 2025 - Sep. 2024

Government Technology Agency (GovTech) Singapore

Data Engineer Intern

Cloud Data Platform Modernization: Optimised Redshift data warehouse performance (-30% storage, -15% latency) and deployed a SageMaker Unified Studio analytics zone (Bedrock, Glue, Athena, DataZone) with Terraform IaC, centralizing data for 50+ users and enabling 100M+ daily clickstream insights via Firehose โ†’ S3 โ†’ Redshift โ†’ Quicksight.

Mar. 2024 - Dec. 2024

DSO National Laboratories

AI Engineer Intern

Multi-Agent RAG System: Built a containerized, graph-based local RAG pipeline (LangGraph + Ollama + Neo4j + PostgreSQL) for research assistance, generating Knowledge Graphs from PDFs and improving multi-hop query accuracy by ~30%, cutting research analysis time by 10+ hours/week.

Jan 2024 - Apr. 2024

Poh Tiong Choon Logistics Ltd.

Data Analyst Intern

Supply Chain Optimization: Analyzed delivery driver datasets with Python & Power BI to improve scheduling and built automated Bash/Python ETL pipelines, boosting driver utilization by ~20% and cutting report time from 8 h โ†’ 1 h.

Photography