SixSense Technologies
SixSense ML Annotation Pipeline (DANN/PIP)
Full rebuild of the SixSense AI platform frontend plus a DANN/PIP annotation pipeline — 50% load cut, +30% engagement, 40% faster annotation.
reduction in page load times
+30%increase in user engagement
faster ML annotation via DANN/PIP pipeline
fewer API calls through intelligent caching and batching
on-time sprint delivery across the engagement
The Problem
The AI platform frontend was slow and losing users; the annotation process was manual and couldn't scale with the ML workload.
What I Built
Led a ground-up rebuild of SixSense's core AI platform frontend using React Fiber architecture, dramatically cutting load times and improving engagement. In parallel, built an ML annotation pipeline (DANN/PIP methodology) that accelerated the semiconductor defect annotation workflow by 40%. Managed a mono-repo spanning 5+ microservices.
Technologies
- React
- React Fiber
- TypeScript
- Python
- DANN/PIP
- Microservices
- Docker
- AWS