Xiao Jun Ang — AI Engineer

About Me

I'm an AI Engineer with hands-on experience building end-to-end ML pipelines and deploying production-grade models across classical ML, computer vision, and Large Language Models. Currently training under AI Singapore's national AI Apprenticeship Programme (AIAP) and pursuing a Master of IT in Business (AI) at Singapore Management University.

My background in Pharmaceutical Science (NUS, Honors Distinction) gives me a unique lens — bridging rigorous scientific methodology with modern machine learning to drive data-informed decisions and scalable AI solutions.

Skills & Expertise

Featured Projects

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Project Alpha

Short description of the project. Highlight the problem solved and the impact delivered.

Python PyTorch MLflow

GitHub Live Demo

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Project Beta

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Docker PySpark MLflow

GitHub Live Demo

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Project Gamma

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LLMs RAG Python

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Work Experience

AI Engineer (AIAP)

AI Singapore

Jan 2026 – Present

Selected for a competitive national AI programme with intensive deep-skilling in AI/ML engineering, followed by an industry project deployment.

Python PyTorch PySpark MLflow Docker Cloud Run RAG LLMs Airflow

Selected for a competitive national AI programme consisting of an intensive deep-skilling phase in high-level AI/ML engineering, followed by an industry project deployment.
Built end-to-end ML pipelines (PySpark, MLflow, Docker, Cloud Run) supporting scalable data preprocessing, model training, evaluation, deployment, and monitoring.
Developed and benchmarked deep learning models (LSTM, CNN architectures) using PyTorch with systematic experimentation and hyperparameter optimization.
Implemented RAG-based knowledge systems combining internal datasets and external scientific literature for domain-specific question answering and decision support.

Machine Learning Engineer

Beeva AI

Sep 2025 – Jan 2026

Developed and fine-tuned deep learning models in PyTorch for computer vision, with production-grade MLOps workflows supporting reproducible research.

PyTorch Computer Vision MLflow DVC Docker Deep Learning

Developed and fine-tuned deep learning models in PyTorch for computer vision applications, with emphasis on generalizable feature learning and robust validation.
Implemented production-grade MLOps workflows (MLflow, DVC, Docker) to support reproducible research and scalable deployment.
Optimized models for latency, inference cost, and deployment constraints, balancing experimental performance with real-world usability.

Research Officer

A*STAR – Nutrition & Digestive Health

Oct 2023 – Jan 2026

Conducted PBPK/PK-PD modelling and quantitative LC-MS/MS analysis to support drug bioavailability research and evidence-based decision-making.

PBPK Modelling LC-MS/MS Python R Data Analysis ADME

Designed and executed in vitro biological and biochemical models (Caco-2 and SHIME®) to quantify compound bioavailability, transport, and functional performance.
Conducted quantitative LC-MS/MS analysis to support PBPK and PK/PD-informed models assessing pharmaco/nutrico/toxicokinetic behaviour of drugs and food ingredients.
Translated biological mechanisms (ADME, transporter kinetics, enzyme interactions) into model-ready parameters to improve clinical prediction accuracy.

Product Development Lead

Craft Health

Jun 2022 – Sep 2023

Led data-driven product development for pharmaceuticals and nutraceuticals, managing a team of five across multiple client projects.

Data Analytics Market Research Product Development Team Management

Led data-driven product development for pharmaceuticals, nutraceuticals, and food & beverage — translating technical and market requirements into actionable plans.
Conducted quantitative market research and trend analysis to identify consumer needs and generate product innovation strategies.
Managed a team of five formulation associates, applying structured methodologies and quality control metrics to ensure reproducibility of outcomes.

Education

Singapore Management University

Master of IT in Business – Artificial Intelligence Track

Current

Recipient of the Richard Lim Lee Scholarship
Coursework: GenAI with LLM, Applied Machine Learning, Machine Learning Engineering, Reinforcement Learning, Recommender Systems, Query Processing & Optimization, Statistical Thinking for Data Science

National University of Singapore

Bachelor of Science in Pharmaceutical Science with Honors (Distinction)

Jul 2022

Ngee Ann Polytechnic

Diploma with Merit in Biomedical Science

May 2018

Recipient of the Merit Scholarship Award, Overseas Merit Award, Fischer Scientific Prize, and Practical Mediscience Prize
Graduated in the top 10% of the Biomedical Science cohort