AI Systems & Full-Stack Engineer with 3+ years of professional experience building production-grade, end-to-end autonomous systems that run with minimal human intervention — spanning industrial computer vision and edge AI, multi-agent LLM orchestration (LangGraph, Model Context Protocol), and full-stack engineering across Go and TypeScript microservices — from real-time ML inference on embedded hardware to cloud-native GCP deployment.
I enjoy designing reliable system architectures end-to-end: contract-first agent/service integrations, low-latency ML pipelines, and cloud deployments that are measurable, testable, and easy to operate. I’ve worked on everything from edge object detection and signal-processing QC systems to multi-agent orchestration layers and microservice migrations.
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EmojiTalks is an AI-powered educational app built with Flutter and Firebase, designed to help 4th–8th grade students improve their English through gamified storytelling. Students create stories from random emojis via text or voice, which are analyzed by NLP models for grammar, vocabulary, and creativity. I developed the mobile app, a React-based teacher/parent panel for class management, and a challenge system where students compete in real time. The app uses RevenueCat for subscription management and is live on App Store & Google Play.
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