Ji-won L.
✓ Vetted CrafterStaff Software Engineer – MVP & Deployment
I build MVPs and deploy them — from concept to production in weeks.
About
I build MVPs and deploy them. I have shipped 5 products from concept to production in 4–8 weeks. My focus is on getting something live fast: Next.js, Vercel, Docker, GitHub Actions. Cursor helps me scaffold apps and write deployment configs. I believe that deployment is part of the product — if you cannot ship it, it does not exist.
I work with TypeScript, Next.js, Docker, and PostgreSQL. I have set up CI/CD for startups, migrated from manual to automated deploys, and built zero-downtime release processes. I deliver MVPs that are production-ready from day one.
AI Expertise
Notable Projects
Smart Factory Worker Safety System
Built a real-time worker safety monitoring system for a Korean automotive parts manufacturer. Uses YOLOv8 for PPE detection (helmets, vests, gloves) and ByteTrack for worker tracking across 40 camera zones. Alerts trigger in under 300ms; dashboard built with React and FastAPI WebSocket streaming.
✓ Workplace safety incidents reduced by 54% in first year; insurance premiums reduced by $180K annually; system passed Korean industrial safety certification.
Multimodal Product Quality Report Generator
Built an application that combines YOLOv8 defect detection on product images with GPT-4 Vision for contextual defect description generation. The system identifies defects, classifies severity, and uses the LLM to write human-readable quality inspection reports in both Korean and English.
✓ Report generation time reduced from 45 minutes to 3 minutes per inspection; defect documentation quality rated higher by QA auditors than manual reports in blind comparison.
Retail Crowd Analytics Platform
Designed a full-stack retail analytics product tracking customer flow, dwell times, and zone heatmaps across department store floors. Built the vision pipeline on YOLOv8 + DeepSORT, deployed on Vertex AI, with a React dashboard and BigQuery data warehouse for historical trend analysis.
✓ Deployed across 12 department stores; store layout optimization guided by analytics data increased revenue per square meter by 11% on average.
Work Experience
Staff Computer Vision Engineer
Kakao
2021 – Present
Lead vision AI for Kakao's commerce and AR features serving 50M+ Koreans. Own the real-time object detection infrastructure and the multimodal AI product strategy.
Computer Vision Engineer
Samsung SDS
2017 – 2021
Built vision AI systems for smart factory applications across Samsung's manufacturing subsidiaries. Delivered defect detection, robotics vision, and worker safety systems in automotive and electronics manufacturing.
Education & Certifications
M.Sc. Electrical Engineering (Computer Vision)
KAIST · 2016
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