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AI Engineer · Video encoder benchmarks for RL control · LLM governance for financial services
I build production AI systems for regulated environments and run independent benchmarks on video foundation models for control. Current work: LLM/RAG systems for Singapore government and financial services — agentic workflows, document intelligence (99.5% extraction accuracy under MAS governance), and AI platform architecture. Last deployment: 300% analyst productivity via RAG + agent orchestration. Independent research: Controlled benchmark on frozen video encoders for RL. V-JEPA 2 (300M params, frozen) reaches 2.4x CNN baseline on continuous control with 0.2% trainable parameters on a single RTX 3080. Three-encoder comparison (V-JEPA 2 vs SigLIP vs DINOv2) — same pipeline, same head, same budget. Published on Substack with full code on GitHub. PyTorch · LangChain · LlamaIndex · LangGraph · Qdrant/Milvus · LoRA/PEFT · GPU inference Previously: Microsoft (Azure AI) · Roche APAC · A*STAR · TUMCREATE (autonomous driving ML)
QUT (Queensland University of Technology)
Bachelor’s Degree, Electrical, Electronics and Communications Engineering
N/A – Present
Technical University of Munich
Software Engineering Essential, edX Professional Certificate Program
N/A – Present
IBM
Dave Leong | AI Engineer | Client Engineering | APAC Gen AI Practice
September 1, 2023 – Present
Singapore · Hybrid
Microsoft
Generative AI | ML | Big Data Cloud Solution Architect
March 1, 2022 – August 1, 2023
Singapore
Roche
Cloud Data Analytics Architect
April 1, 2021 – February 1, 2022
Singapore
National Library Board
Cloud Solutions Architect | AI | Machine Learning | Data Analytics | NLP | Data Engineering| Spark |
April 1, 2019 – March 1, 2021
Singapore
A*STAR - Agency for Science, Technology and Research
Senior Industry Software Development Engineer | AI | Deep Learning | Data Analytics | IIoT | AR |
May 1, 2018 – April 1, 2019
Singapore
Technical University Munich
Deep Learning System Developer | Deep Learning | Self Driving Car Data Engineer | TUMCREATE |
May 1, 2017 – April 1, 2018
Singapore
IBM- Learning Watson Analytics
June 24, 2026 – Present
Data Science Foundations: Data Mining
June 24, 2026 – Present
Data Science- The Essential Elements of Predictive Analytics and Data Mining
June 24, 2026 – Present
The Essential Elements of Predictive Analytics and Data Mining
June 24, 2026 – Present
Tableau 10 for Data Scientists
June 24, 2026 – Present
Tableau Essential Training
June 24, 2026 – Present
Data Visualization in R with ggplot2
June 24, 2026 – Present
Data Science- R for Excel Users
June 24, 2026 – Present
Others- MATLAB 2018 Essential Training
June 24, 2026 – Present
Others- Learning MATLAB
June 24, 2026 – Present
Data Engineering- Advanced SQL for Data Science: Time Series
June 24, 2026 – Present
Data Engineering- Learning Linux Shell Scripting
June 24, 2026 – Present
Linux: Bash Shell and Scripts
June 24, 2026 – Present
Cloud Computing with IBM Bluemix
June 24, 2026 – Present
AWS- Building Intelligent Chatbots on AWS
June 24, 2026 – Present
Data Science of Economics, Banking, and Finance
June 24, 2026 – Present
Data Science of Retail, Sales, and Commerce
June 24, 2026 – Present
Data Science of Healthcare, Medicine, and Public Health
June 24, 2026 – Present
Data Science of Sports Management
June 24, 2026 – Present
Apache PySpark by Example
June 24, 2026 – Present
IBM Watson | Build Chatbots with Watson Conversation | Personalized Conversational Interface | NodeJS | React
IBM
June 24, 2026 – Present
AWS- Supervised Machine Learning | Business use case Call Center | Intelligent Call Routing Controller |
Amazon Web Services (AWS)
June 24, 2026 – Present
Technical Sales: The Role of the Sales Engineer
June 24, 2026 – Present
Predictive Customer Analytics | E-commerce | Azure & IBM Python Notebook
June 24, 2026 – Present
NLP with Python for Machine Learning Essential Training
June 24, 2026 – Present
Introduction to Spark SQL and DataFrames
June 24, 2026 – Present
Building Recommender Systems with Machine Learning and AI
June 24, 2026 – Present
Developing on AWS Pinpoint for Analytics and User Engagement
June 24, 2026 – Present
Data Science of Government and Political Science
June 24, 2026 – Present
Amazon Web Services Machine Learning Essential Training
June 24, 2026 – Present
Enterprise Architecture Foundations
June 24, 2026 – Present
AWS- Cert Prep: AWS Certified Solutions Architect - Professional
June 24, 2026 – Present
Cloud Architecture: Core Concepts
June 24, 2026 – Present
Advanced SQL for Data Scientists
June 24, 2026 – Present
Advanced SQL for Data Science: Time Series
June 24, 2026 – Present
Data Engineering- Learning Hadoop
June 24, 2026 – Present
Data Engineering- Extending Hadoop for Data Science: Streaming, Spark, Storm, and Kafka
June 24, 2026 – Present
Data Science of Nonprofit Service Organizations
June 24, 2026 – Present
Certificate of Completion of Databricks Lakehouse Fundamentals
Databricks
June 24, 2026 – Present
Certificate of Completion of Fundamentals of the Databricks Lakehouse Platform Accreditation
Databricks
June 24, 2026 – Present
AWS Introduction to Amazon Comprehend Certificate of Completion
Amazon Web Services (AWS)
June 24, 2026 – Present
AWS Introduction to Amazon Elastic MapReduce (EMR) Certificate of Completion
Amazon Web Services (AWS)
June 24, 2026 – Present
AWS Job Roles in the Cloud Certificate of Completion
Amazon Web Services (AWS)
June 24, 2026 – Present
AWS Well-Architected Certificate of Completion
Amazon Web Services (AWS)
June 24, 2026 – Present
AWS Technical Essentials Certificate of Completion
Amazon Web Services (AWS)
June 24, 2026 – Present
AWS Cloud Practitioner Essentials Certificate of Completion
Amazon Web Services (AWS)
June 24, 2026 – Present
Azure- Advanced Microsoft Power BI
June 24, 2026 – Present
Azure- Power BI Mistakes to Avoid
June 24, 2026 – Present
Azure Administration: Deploy and Manage Virtual Machines
June 24, 2026 – Present
Azure Administration: Manage Identities
June 24, 2026 – Present
Azure Administration: Configure and Manage Virtual Networks
June 24, 2026 – Present
Azure Essential Training for Developers
June 24, 2026 – Present
Azure Cosmos DB: Import, Manipulate, Index and Query
June 24, 2026 – Present
Azure- Scaling Applications with Microsoft Azure
June 24, 2026 – Present
Azure- Developing CI/CD Solutions with Azure DevOps
June 24, 2026 – Present
Azure Administration: Implement and Manage Application Services
June 24, 2026 – Present
Azure Administration: Load Balancers and Application Gateways
June 24, 2026 – Present
Azure Serverless Computing
June 24, 2026 – Present
Azure Administration: Implement and Manage Storage
June 24, 2026 – Present
IBM watsonx Essentials
IBM
June 24, 2026 – Present
watsonx.data Sales Foundation
IBM
June 24, 2026 – Present
Building Smart Business Assistants with IBM Watson
Coursera
June 24, 2026 – Present
watsonx.governance Level 2
IBM
June 24, 2026 – Present
IBM watsonx Foundations
IBM
June 24, 2026 – Present
ChatGPT: Complete ChatGPT Course For Work 2023 (Ethically)!
Udemy
June 24, 2026 – Present
C r e a t e a C h a t G P T AI B o t with Tkinter and Python
Udemy
June 24, 2026 – Present
ChatGPT: The Complete ChatGPT Guide from Zero to Hero (2023)
Udemy
June 24, 2026 – Present
ChatGPT Masterclass: A Complete ChatGPT Guide for Beginners
Udemy
June 24, 2026 – Present
The Complete ChatGPT Web Development Code Along - Javascript
Udemy
June 24, 2026 – Present
Microsoft Azure Synapse for Developers
June 24, 2026 – Present
Snowflake Fundamentals 4-Day
Snowflake
June 24, 2026 – Present
Microsoft Azure for Data Engineering
Coursera
June 24, 2026 – Present
watsonx.governance Sales Foundation
IBM
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across IBM, Microsoft, Roche, National Library Board, A*STAR, and Technical University Munich demonstrates adaptability to various organizational cultures, from large enterprises to government agencies and research institutions. Their involvement in projects with significant societal impact (e.g., improving analyst productivity for government, traffic control, national library content discovery) suggests a mission-driven mindset. The breadth of certifications, while numerous, indicates a continuous learning attitude and a willingness to acquire new skills, which is a positive cultural indicator. The target role of ML Engineer aligns perfectly with their recent and past experience in AI/ML system design and deployment.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight a strong focus on problem-solving, strategic decision-making (e.g., trade-off analysis), and leadership in establishing data centers of excellence and leading team skill development. The emphasis on 'trust, auditability, and knowing when the system is wrong' indicates a mature, responsible approach to AI deployment, which aligns well with operational excellence in complex environments.