: Jeayoung Jeon
MLOps and Cloud-Native Engineer
- Location
- Anyang & Seoul, South Korea
- jyjeon@outlook.com
- GitHub
- GitHub: jyje
- Google Scholar
- Google Scholar:
- GitHub
- Github
- StackShare
- StackShare
- Google Scholar
- Google Scholar
Work
– present
Project Widearth: Digital Twin Platform with AR/VR at MAXST
Project Widearth: Point-cloud-based spatial mapping platform for digital twins. I am responsible for the development of ML pipelines, APIs and Infrastructure:
Highlights
- ML Pipeline Design ML data pipelines using Argo Workflows and Hera Python SDK.
- API Making endpoints for the ML pipeline inference based on Python FastAPI.
- Infrastructure Building hybrid clusters with AWS EKS and bare-metal Kubernetes to reduce costs but keep system reliabilities. Hybrid clusters can reduce public cloud costs by more than 50%.
– present
MLOps/DevOps Engineer at MAXST
Development of on-premise clusters providing DevOps and MLOps for Technology Division in MAXST:
Highlights
- AutoML Making AutoML tuning hyperparameters with Katib and Argo Workflows without pre-build.
- Data Lake Storing pipeline results into storage and RDB. Visualizing with Grafana and Tensorboard.
- JupyterHub Generating On-Demand JupyterNotebook to distribute resources for ML researchers.
- CI/CD Designing Slackbot providing GitOps: Bitbucket Pipeline, Argo Workflows and Argo CD.
- On-Premise Building bare-metal Kubernetes clusters using IaC tools such as Ansible.
–
Computer Vison Engineer at MAXST
Developing computer vision algorithms for AR/VR and Digital Twin Systems.
Highlights
- Visual-SLAM Research for Digital Twin Systems
- Developing ICP Algorithm to Align 3D Point Clouds
–
Student Researcher with Integrated Program at POSTECH
Studying and researching in the field of digital signal processing and computer vision. During my time as a graduate student at POSTECH, I had the privilege of working in several projects:
Highlights
- 2018 - 2020 Computing and Control Engineering Lab.
- 2012 - 2018 Advanced Signal Processing Lab.
- Stereo Vision Algorithms for Image Depth Estimation
- Real-Time Advanced Driver Assistance Systems using FPGA
- Lane Mark and Traffic Sign Detection
- Automotive Online Calibration in Stereo Vision
