Tridge
AI-Powered News Classifier
LLM news classification and backend processing at Tridge.
담당 업무Develop the classifier, compare model versions, and improve processing algorithms.
프로젝트 상세 보기EJ Caliwag · 대한민국 서울 · UTC+9
응용 AI, 백엔드 시스템, 배포를 아우르는 일을 합니다. Tridge의 LLM 뉴스 분류, Tricubics의 컴퓨터 비전, 엣지–클라우드 연구 경험이 있습니다.
원격·하이브리드·상주 근무 가능 · 이주 가능
한국 체류: F 계열 비자 보유
주요 프로젝트
문제, 담당 업무, 기술적 접근을 중심으로 정리한 실무 프로젝트와 연구입니다.
포트폴리오 어시스턴트 체험 →출처를 확인할 수 있는 대화형 데모입니다.
Tridge
LLM news classification and backend processing at Tridge.
담당 업무Develop the classifier, compare model versions, and improve processing algorithms.
프로젝트 상세 보기Tricubics
Computer vision, tracking, and deployment for an unmanned vending service.
담당 업무Lead AI/software integration across detection, tracking, decision logic, and deployment.
프로젝트 상세 보기Kumoh National Institute of Technology
Published research into face-recognition inference across edge and cloud systems.
담당 업무Co-author the Sensors paper on collaborative edge–cloud inference.
프로젝트 상세 보기경력
Tridge - Backend Department AI Team · South Korea
As an Assistant Manager on the AI Team within the Backend Department at Tridge, I am developing a news classifier leveraging large language models (LLMs). My work involves testing multiple versions of the model and implementing algorithms to enhance processing speed. I also contribute to improving the overall performance and efficiency of company systems.
Tricubics - Research & Development (R&D) · South Korea
Oversee end-to-end service management for the unmanned vending machine system, including team progress tracking and scheduling. Designed and maintained DevOps processes using Docker and Kubernetes to support system updates and modifications. Applied YOLOv8 for object detection, optimizing performance with TensorRT; used MobileNetV3 for classification tasks. Implemented object tracking algorithms based on ByteTrack and DeepSORT. Developed a decision-making algorithm leveraging a 'frame zone' approach to enhance system intelligence. Integrated ZeroMQ for lightweight messaging protocol support. Added optional MongoDB integration for storing external transaction data.
Data Design Engineering · South Korea
Image segmentation using U-Net architecture. Collaborate on writing algorithms as well as training a YOLOv5 and YOLOv7 model for book spine detection. Develop, train, and deploy a face detection model to an embedded board developed by KT&C. System automation and data pipeline handling using Apache Airflow, Docker, and AWS. Writing of Python scripts for crawling purposes. Database management including PostgreSQL and MongoDB.
연구
연락하기
응용 AI, 백엔드, 풀스택 AI 엔지니어 직무에 관심이 있습니다. 서울에 거주하며 이주 가능합니다.