Aman Zainal
AI Engineer · Singapore
Aman Zainal is a Singapore-based engineer and former founding AI engineer at AIRAP. He graduated from the National University of Singapore in Computer Science and Mechanical Engineering as an ASEAN Scholar (Ministry of Education, Singapore). He builds production AI products that survive past the demo — aviation compliance audit tools, B2B operations platforms, research interpretability layers, and generative AI pipelines on a local 4-GPU rig. He is available now for full-time roles and collaborations.
Download résumé (PDF)
Selected work
- AIRAP / Aero Plus Platforms — aviation compliance audit, AI-brokered aircraft-parts marketplace, and EASI B2B ordering platform. ~95% analyst-graded audit accuracy; EASI shipped in two weeks by a two-engineer team.
- Forecast Interpreter (A*STAR ARTC) — conversational interpretability layer over A*STAR's internal demand-forecasting models. Cuts planner workflow from ~40 minutes to ~2 minutes per forecast.
- Hyundai Singapore (HMGICS) — DevOps engineer; planned and drove a monolith-to-19-server service-isolation migration and built ThingWorx applications for HMGICS's connected-manufacturing platform.
- Banyan — collaborative family-tree app with realtime graph rendering and share-link onboarding. Next.js 16, Supabase Realtime + RLS, React Flow.
- Virtual Wardrobe — generative AI clothing try-on platform; FastAPI gateway, Vite/React web, Expo React Native, ComfyUI on RunPod GPU.
- Real or AI eye test — twelve-plate guessing game; half public-domain photos, half generated locally on the 4-GPU rig.
Site map
- Work — production systems shipped with real users
- Projects — independent builds, tools, and experiments
- About — background, capabilities, current role
- Real or AI — eye-test game powered by local diffusion models
- Stack — the image-pipeline rig
- Contact — Telegram, email, GitHub, LinkedIn
- Resume (PDF)
Elsewhere
Find Aman Zainal on GitHub, LinkedIn, and Telegram. Email: aman@u.nus.edu.