Résumé: Jeayoung Jeon

MLOps and Cloud-Native Engineer

My name is Jeayoung Jeon [🇰🇷전제영], and I’m a software engineer in South Korea. I’m developing my career with the synergy of Computer Vision Research Experience and Cloud-Native Engineering Experience. Here is my career history:

DurationCompanyPositionRole
2021.01-2024.10 [3Y,10M]MAXST, Technology DivisionSeniorMLOps/DevOps & Computer Vision Engineer
2012.03-2020.08 [8Y,6M]POSTECH, Department of Electrical EngineeringIntegratedAutomotive & Computer Vision Researcher
2008.03-2012.02 [4Y]kit, School of Electronic EngineeringBachelorInformation Communication & Digital Signal Processing
I’m passionate about collaboration culture and automation that can achieve the best results with fewer people. I’m always looking for the optimal way to achieve both performance improvement and cost reduction. Based on my experience and achievements, I hope to have a career that grows with the company. For more details, please visit my portfolio and blog (Korean).
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Email
LinkedIn
LinkedIn: jyje
Google Scholar
Google Scholar: Jeayoung Jeon
GitHub
Github
StackShare
StackShare

Projects

– (10 Months)

🧑‍💻 Widearth: Digital Twin Platform with Spatial Map & AR Contents at MAXST

Roles: Development of ML pipelines, APIs and Infrastructure
  • DevOps Designed CI/CD pipelines for web servers and ML workloads. Set git-flow environments with GitOps and led decision-making for deployments.
  • Hybrid Cluster Built hybrid clusters with AWS EKS and bare-metal Kubernetes. The ML pipelines are executed on on-premise clusters to optimize GPU costs. Backup pipelines are configured on EKS to increase availability.
  • ML Pipeline & API Designed Argo Workflows based ML data pipelines to generate spatial maps. Developed cloud-native API endpoints managing lifecycle of pipelines.
Results: 'Contribute Dev & Ops' <- Built Hybrid Clusters, ML Pipelines, and CI/CD Pipeline [contrib 75%+]
  • Main DevOps Manage CI/CD for Widearth project. Leading 40+ deployments for 3 months.
  • Robust Hybrid Infra Achieved '96% availability/year and 14d downtime' using hybrid clusters and DevOps support.
  • ML Pipeline Designed ML APIs and data pipelines in multi-clusters. Reduces costs of public cloud by 50%.
Skills: Core Skills for Project Widearth
  • AWS EKS
  • Karpenter
  • Python FastAPI
  • Argo Workflows
  • Argo CD

– (6 Months)

🧑‍🔬 MLOps: On-premise MLOps with the Latest Open Source Projects at MAXST

Roles: Built Core MLOps Platform using CNCF Open Source Projects
  • AutoML Making AutoML tuning hyperparameters with Katib and Argo Workflows without pre-build.
  • Distributed Training Developing distributed learning environments using Kubeflow Training Operator.
  • JupyterHub Developed a platform for managing on-demand Jupyter Notebooks, allowing researchers to instantly configure their required research environment.
Results: 'Initiate MLOps' <- Improve GPU utilization for AI research using Kubeflow, JubeterHub [contrib 90%+]
  • MLOps Applied latest open sources to improve the on-premises research environment.
  • GPU Utilization Increased GPU utilization by 3 times and conducted more than 800 AutoML experiments.
Skills: Core Skills for On-Premise MLOps
  • Kubeflow/Katib
  • Kubeflow/Training Operator
  • Argo Workflows
  • Grafana
  • TensorBoard

– (12 Months)

🧑‍🔧 DevOps: Development of Hybrid Clusters Providing CI/CD and Chatbot at MAXST

Roles: Development of Hybrid Clusters, CI/CD Pipelines, and Chatbot
  • Hybrid Cluster Built a hybrid cluster with AWS EKS and on-premise Kubernetes. GPU workloads are executed on on-premise clusters to optimize costs. Web and backup workloads are configured on EKS to increase availability.
  • IaC IaC with Terraform and Ansible to manage the cluster infrastructure: Terraform to set up AWS EKS cluster. Ansible-based Kubespray to set up on-premises cluster.
  • CI/CD Configured fast CI for collaboration using Bitbucket Pipeline. Configured high-performance custom CI using on-premises Argo Workflows. Implemented CD using GitOps with Argo CD and Slackbot. IaC was also configured as CI/CD and pipeline to set up declarative infrastructure.
Results: 'Initiate DevOps' <- Developed Hybrid Clusters using AWS EKS and On-Premise [contrib 75%+]
  • Robust Hybrid Cluster Achieved 50%+ cost reduction compared to pure cloud infrastructure using on-premises cost-effectiveness.
  • DevOps Culture Propagation of DevOps culture including app modernization and CI/CD. Decision support through monitoring.
Skills: Core Skills for Hybrid DevOps
  • Kubernetes
  • Argo Workflows
  • AWS EKS
  • IaC
  • Terraform
  • Python/FastAPI
  • Python/Bolt (Slack)

– (2 years)

📸 Digital Twin Research Engineer at MAXST

Roles: Development of computer vision algorithms and construction of digital twin systems
  • Visual-SLAM & SfM Developed digital image processing algorithms for Visual-SLAM and SfM. Constructed a digital twin system using image processing algorithms.
  • Technical Research Personnel Engaged in computer vision positions related to graduate school majors and performed military alternative service.
Results: 'Proof of Concepts' <- Algorithm research for digital twin systems [contrib 50%]
  • Digital Twins Research and development of Visual-SLAM and ICP algorithms for digital twin systems
  • Automation Development of automated pipelines for data acquisition and analysis
Skills: Core skills for digital twin research
  • Computer Vision
  • SfM
  • Visual-SLAM
  • Python
  • OpenCV
  • .NET/C#
  • Unity

– (8 Years)

🧑‍🎓 Digital Signal Processing and ADAS Researcher (Integrated Program) at POSTECH

Roles: Studying and researching in the field of digital signal processing and computer vision
Results: 'R&D' <- Studying on Automotive Simulations in Virtual Environments and ADAS On-Edge.
  • Digital Twins Virtual Visual-SLAM for Real-World Environments
  • Edge ADAS Research of ADAS including Traffic Sign Detection & Lane Terrain Detection with FPGA
Skills: Core Skills for ADAS Research
  • Computer Vision
  • Digital Signal Processing
  • Markov Random Fields
  • ADAS
  • Traffic Sign Detection
  • Lane Terrain Detection
  • MATLAB/Simulink
  • C/C++

Work

– present

💼 Senior Software Engineer [🇰🇷 책임연구원] at MAXST

Roles: Developed On-Premise Clusters Providing MLOps for Technology Division in MAXST
  • MLOps Architecting and optimizing on-premise Kubernetes clusters to deliver comprehensive MLOps solutions
  • DevOps Building hybrid clusters with AWS EKS and bare-metal Kubernetes. Participated in projects as a DevOps role, contributing to service launches. Propagated DevOps culture, including CI/CD configuration and app modernization.
  • Hybrid Implemented and operated hybrid clusters combining AWS EKS and on-premises Kubernetes. Built on-premises clusters using Ansible and Kubespray, and configured AWS EKS clusters using Terraform.
Skills
  • Kubernetes
  • On-Premise
  • AWS
  • Argo Workflows
  • Data Pipeline
  • CI/CD
  • Computer Vision
  • OpenCV

– (3 Years)

💼 Software Engineer [🇰🇷 선임연구원] at MAXST

Roles: Associate R&D Engineer for Technology Division in MAXST
  • Algorithm Research Reviewing computer vision algorithms in state-of-art papers and implementing prototypes.
  • DevOps Building hybrid clusters and providing data pipelines for digital twins.
  • Technical Research Personnel Serving as a substitute for military service for 3 years, engaging in the industry in the related field of computer vision major.
Skills
  • Kubernetes
  • On-Premise
  • AWS
  • Argo Workflows
  • Data Pipeline
  • CI/CD
  • Computer Vision
  • OpenCV

Education

–

🎓 Master's Degree (Integrated Program) in Department of Electrical Engineering, Signal Processing & Computer Vision from Pohang University of Science and Technology (POSTECH) with GPA of 3.2/4.3

–

🎓 Bachelor's Degree in School of Electronic Engineering, Electronic Communication from Kumoh National Institute of Technology (kit) with GPA of 4.3/4.5

Certifications

(Expired in )

🐈‍⬛ GitHub Foundations from GitHub

A credential that verifies expertise in version control and collaboration tools using GitHub.

(Expired in )

🐙 CAPA: Certified Argo Project Associate from The Linux Foundation

A credential that verifies expertise in the Kubernetes native DevOps tool, Argo Projects

(Expired in )

🐳 CKAD: Certified Kubernetes Application Developer from The Linux Foundation

A credential that verifies expertise in developing cloud-native applications using Kubernetes.

(Expired in )

🐳 CKA: Certified Kubernetes Administrator from The Linux Foundation

A credential that verifies expertise in managing Kubernetes clusters.

Skills

Here are my skills and highlighted items are industry-ready.

MLOps & LLMOps
Keywords:
  • Kubeflow
  • Data Pipeline
  • AutoML Katib
  • Training Operator
  • JupyterHub
  • PyTorch
  • OpenCV
  • Ollama
  • RAG
  • OpenAI
DevOps
Keywords:
  • Kubernetes
  • Argo Workflows
  • AWS EKS
  • Kubespray
  • IaC
  • Terraform
  • Ansible
  • Grafana
  • Karpenter
GitOps
Keywords:
  • CI/CD
  • Argo CD
  • Bitbucket Pipelines
  • GitHub Actions
  • Kaniko
  • Docker/Multi-stage
  • Slackbot
Application Development
Keywords:
  • Python/FastAPI
  • Unit Testing
  • .NET/WPF
  • .NET/MAUI
  • Unity
Programming languages
Keywords:
  • Python
  • C#
  • C/C++
  • Go
  • MATLAB
Tool, OS and Hardware
Keywords:
  • Visual Studio Code
  • Visual Studio
  • Jupyter Notebook
  • MATLAB/Simulink
  • Windows
  • WSL2
  • Ubuntu
  • Alpine
  • MacOS
  • ARM64/Raspberry Pi
  • AMD64/Bare Metal
  • FPGA

Interests

Edge
Keywords:
  • Raspberry Pi Cluster
Cluster Optimization
Keywords:
  • Karpenter
  • BI using Grafana (PLG)
CNCF Projects
Keywords:
  • Kubeflow
  • Argo Projects

Languages

Korean
Fluency: Native
English
Fluency: Working Proficiency