date
Jan 5, 2024
slug
resume
author
status
PublicOnDetail
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summary
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Paper
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updatedAt
May 8, 2025 04:11 PM
David Chong
Senior Software Engineer
Contact.
Email. davidcjw@gmail.com
Channel.
GitHub. https://github.com/davidcjw
Blog. https://davidcjw.com
Medium. https://medium.com/@davidcjw
Introduction.
I am an economics undergrad turned software engineer. My career path has been anything but linear. I joined an investment bank upon graduation and found myself doing data analytics and so I pivoted to study a part-time Masters in AI and eventually landed my foot into AI engineering. I grew my interest in the infrastructure aspects of ML and pivoted yet again into MLOps. More recently, I pivoted more towards DevOps and platform engineering, now involved in Cloud Native engineering.
Work Experience.
Senior Software Engineer
2023.10 - Present
- Responsible for day to day operational maintenance of Data Science analytics infrastructure (JupyterHub, Airflow, Dask & MLFlow) and ETL pipelines (using SQL, Airflow)
- Overhauled previously used Data Science infrastructure from single VMs to JupyterHub on GKE alongside parallel computing with Dask, reducing infrastructure and model training cost by ~60%
- Principal contributor and maintainer of internal data science Python library used by all members of the Data Science team, improving model development efficiency
- Automated CICD pipelines for deployment of batch (Airflow) and real- time models (APIs), reducing deployment time by 50%
- Continually innovate and optimize team’s ML workflow
Tech Stack
GCP, Kubernetes, Python, Golang, Airflow, MLFlow, Gitlab, Dask, Bash, PostgreSQL
Main Contributions
- Responsible for day to day operational maintenance of Data Science analytics infrastructure (JupyterHub, Airflow, Dask & MLFlow) and ETL pipelines (using SQL, Airflow)
- Overhauled previously used Data Science infrastructure from single VMs to JupyterHub on GKE alongside parallel computing with Dask, reducing infrastructure and model training cost by ~60%
- Principal contributor and maintainer of internal data science Python library used by all members of the Data Science team, improving model development efficiency
- Automated CICD pipelines for deployment of batch (Airflow) and real- time models (APIs), reducing deployment time by 50%
- Continually innovate and optimize team’s ML workflow
Tech Stack
GCP, Kubernetes, Python, Golang, Airflow, MLFlow, Gitlab, Dask, Bash, PostgreSQL
Main Contributions
Worked on 2 end-to-end projects:
1) Content classification in a
digital marketing domain for a regional AI-based startup
- Led a team of 3 engineers to develop a multi-modal content-classification model (text, image & emojis)
2) Recommender System (RecSys) for a local university library.
- Led the development of a library recommender system that consisted of two components (a) an API endpoint (real-time & non-personalized) used by web frontend and (b) scheduled email recommendations (batch & personalized)
Effective in communicating complex ideas and concepts to clients
Tech Stack
AWS, Kubernetes (OpenShift), Python, FastAPI, Gitlab, W&B, DVC, MLFlow
Main Contributions
Principal engineer who spearheaded the development of the end-to-end PDF to infographic service, from conceptualization to deployment
Integrated AI algorithms into front-end user interfaces, ensuring a seamless and intuitive user, including a payment gateway via Stripe
Tech Stack
AWS, Python, HTML/CSS, Typescript + Vue 3, FastAPI, PostgreSQL, DVC, GitHub Actions, Terraform, Stripe API
Education.
Singapore Management University
Masters of IT in Business (Artificial Intelligence Track)
2018 - 2020
Intro to Artificial Intelligence
Applied Machine Learning
Data Management
Computer Vision
Social/Text Analytics
Big Data Tools & Techniques
Natural Language Processing
Algorithm Design
Recommender Systems
Singapore Management University
BSc (Economics and Finance)
2013 - 2017
Dean’s List AY 2013/2014
Dean’s List AY 2014/2015
High Distinction in Statistics, Game Theory & Analysis of Derivatives Securities
Teaching Assistant for Game Theory
Skills.
I’ve a wide range of skills as I started from an AI Engineer and transitioned to MLOps. I can categorise my skillsets into a few buckets:
Data Science: Python | Jupyter | Scikit-Learn | Keras Tensorflow | Pytorch | Streamlit | JupyterHub | Airflow | MLFlow | W&B
Frontend: HTML/CSS/Javascript | Vue.js | Typescript
Backend: Flask | FastAPI | Docker | Git/Gitlab | MySQL | CI/CD | DVC | PostgreSQL | OpenShift | Kubernetes | Cloud services | Bash