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Software Engineer building AI systems that survive contact with production.
01.Signal, not noise
I build AI systems that actually ship — the unglamorous, load-bearing part of machine learning where models meet Docker containers, message queues, and production traffic.
My strongest work sits at the intersection of ML and software engineering: turning models, image-processing pipelines, APIs, databases, and deployment infrastructure into systems that run reliably at scale. Most recently that means an AI-powered PCB inspection platform — board scanning, component analysis, multi-board comparison, real-time inference.
I also evaluate frontier-model outputs for code generation, reasoning quality, and tool use — which has sharpened my sense for the difference between code that looks correct and code that is actually reliable.
02.Deployment history
Cybord AI
2025 — Present- ▸Engineered the microservice backend for a PCB inspection POC — board scanning, component analysis, multi-board comparison — accepted by SpaceX and now in production.
- ▸Built a production desktop app (Electron + FastAPI) integrating proprietary AI models with real-time inference.
- ▸Cut pipeline processing time from ~10 minutes to ~1 minute with task-graph parallelization; reduced model inference time by 60%.
- ▸Fine-tuned computer vision models to 95% production accuracy and automated visual data extraction, saving 200+ engineering hours monthly.
DataAnnotation
2024 — Present- ▸Evaluate frontier-model outputs: code generation, debugging, reasoning quality, and instruction following.
- ▸Identify failure modes in multi-step reasoning, tool-use workflows, and agentic coding tasks.
- ▸Surface the subtle issues automated benchmarks miss — plausible-but-wrong code and unsafe implementation choices.
Vanilla Transtechnor
2021 — 2022- ▸Built scalable web applications serving 5,000+ daily active users with Django REST Framework and React.
- ▸Standardized auth across 12+ microservices with custom middleware, permission classes, and mixins.
- ▸Automated deployment pipelines, cutting deployment time by 40%.
Eightsquare
2019 — 2021- ▸Pioneered a mobile SDK for Malaysian identity-document OCR (IDs, passports, visas), 80% faster through OpenCV optimization in C++/JNI.
- ▸Shipped face recognition + liveness detection SDK — 97% accuracy, 10,000+ daily authentication requests.
- ▸Architected a multi-tenant push-notification SaaS for 50+ enterprise clients at 99.8% uptime.
- ▸Built an employee management system serving 60,000+ employees with role-based access control.
03.Systems in the wild
PCB Inspection Platform
AI-powered board scanning, component analysis, OCR/marking extraction and multi-board comparison. The POC backend was accepted by SpaceX; now running in production.
Real-time Inference Desktop App
Production Electron + FastAPI desktop application integrating proprietary AI models with a multiprocessing inference pipeline for enterprise deployment.
Identity Document OCR SDK
Android SDK for Malaysian ID cards, passports and visas — real-time image processing through OpenCV via JNI (C++), tuned for on-device speed.
Face Recognition & Liveness SDK
Face recognition and liveness detection under varied real-world conditions, processing 10,000+ authentication requests daily.
Multi-tenant Push Platform
Push-notification SaaS supporting 50+ enterprise clients, plus an employee management system serving 60,000+ users with role-based access.
Frontier Model Evaluation
Structured evaluation of frontier-model code generation and agentic tool use — comparative rankings and failure-mode analysis for RLHF pipelines.
04.Toolchain
05.Open a connection
Production ML, computer vision, AI infrastructure — if you're building something real, open a channel. No naked email address on this page; the terminal handles delivery and the scrapers starve.
$ scp resume.pdf ./local ↓