Résumé: Jeayoung Jeon

AI Platform Engineer

🇰🇷 한국어 버전은 여기에서 확인할 수 있습니다.

I’m Jeayoung Jeon [전제영], an AI Platform Engineer in Seoul with about six years of experience. I specialize in:

  • 🐳 GenAI development: Implementing and operating GenAI workloads and LLMOps platforms in cloud-native environments.
  • 🤝 Team leadership: Leading collaboration, architecture, and platform engineering in teams of about ten.
  • 🧑‍🔧 Architecture: Building hybrid Kubernetes clusters for high performance, high availability, and GPU optimization.
  • 🧑‍🎓 Technical expertise: Contributing to LLM, ML, DevOps decisions with backgrounds in Computer Visions and Automotives.
I’m open to new challenges in automotive, AI, and beyond. Please feel free to contact me if you have a team I can contribute to. For details, see my portfolio.
PDF
Email
Website
https://jyje.online
LinkedIn
LinkedIn: jyje
GitHub
Github
StackShare
StackShare

Work

– present (13 Months)

🧑‍💻 Intermediate Software Engineer [책임, Professional] at Hyundai AutoEver

Roles: Lead AI Platform Engineer at Development Environment Platform Team, Hyundai AutoEver
  • AI/LLM Platform Developing extensible AI agents for in-house toolchains and LLMOps configuration
  • Cloud-Native AI Applying k8s+AI in practice and advising team members

– (3 Years 10 Months)

🧑‍🔬 Intermediate Software Engineer [선임-책임연구원] at MAXST

Roles: Lead MLOps/DevOps Engineer at Technology Division, MAXST
  • MLOps/LLMOps Designed ML APIs and data pipelines. Built RAG+LLM systems for enterprise solutions
  • Infrastructure Architected hybrid clusters (AWS EKS + On-Premise) for digital twin platform
  • SRE Led site & service reliability engineering initiatives for web services and ML workloads

– (8 Years 6 Months)

🧑‍🎓 Graduate Student Researcher in Computer Vision at POSTECH

Roles: Ph.D Integrated Student at Department of Electrical Engineering, POSTECH
  • Computer Vision Research on hyperparameters for accurate and efficient computer vision algorithms
  • Automotives Principal computer vision technologies for autonomous driving including ADAS and SLAM; Participated in the development of the Korean government's incubation projects with various ADAS researches
  • FPGA Efficiently implemented computer vision and machine learning algorithms with real-time parallel matrix processing; SoC-type GPU/NPU accelerator

Education

– (8 Years 6 Months)

🎓 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

Thesis

- Thesis: Virtual Visual-SLAM for Real-World Environments, 2020

– (4 Years)

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

Thesis

- Thesis: A Study on a Visible Light Communication using LED in Under-water Environment, 2011

Awards

🏅 Best Poster Session from KYUTECH-POSTECH Joint Workshop

[Poster] Iterative Polygon Detection using Harris Corner Space Method for Finding Traffic Signs

🏅 Summa Cum Laude from Kumoh National Institute of Technology

Highest Honors in Undergraduate Electronic Engineering School, 2012

🏅 NAVER Power KiN 2011 from NAVER

Knowledge Expert in `Electronics Engineering, Math and Programming`. 723 Answers, Accepted 98.1%

Publications

Full list is available on Google Scholar.

, POSTECH, Thesis (1st)

🎓 Virtual Visual-SLAM for Real-World Environments by Jeayoung Jeon

Innovative middle-out compression algorithm that changes the way we store data.

, ISVC, Advances in Visual Computing, 10th International Symposium (2nd)

📄 Cost Aggregation Table: Cost Aggregation Method Using Summed Area Table Scheme for Dense Stereo Correspondence by JeongMok Ha, Jeayoung Jeon, GiYeong Bae, SungYong Jo & Hong Jeong

, ICCAS, 14th International Conference on Control, Automation and Systems (1st)

📄 Polygonal symmetry transform for detecting rectangular traffic signs by Jea Young Jeon, JeongMok Ha, Sung Yong Jo, Gi Yeong Bae, Hong Jeong

, ICS-KIEE (1st, equivalent)

🎓 A Study on a Visible Light Communication using LED in Under-water Environment by Daehee Lee, Ki-Sung Park, Jea-Young Jeon, Yeon-Mo Yang

Skills

Highlighted items are specialized in industry-ready.

GenAI & LLMOps
Keywords:
  • Public/On-Premise LLM
  • RAG
  • MCP
  • Agentic AI
MLOps
Keywords:
  • Kubeflow
  • AutoML Katib
  • Training Operator
  • JupyterHub
DevOps & SRE
Keywords:
  • Kubernetes
  • On-Premise
  • AWS EKS
  • GCP GKE
  • Hybrid Clusters
  • ARM64
  • IaC
  • Kubespray
  • Terraform
  • Ansible
  • Istio
  • Grafana Stack
  • Karpenter
CI/CD/CT/CT
Keywords:
  • Argo Projects
  • Bitbucket Pipelines
  • GitLab CI
  • GitHub Actions
  • Self-Hosted Runner
  • Kaniko
  • Buildah
  • Locust
  • Litmus
ML Backend
Keywords:
  • Python/FastAPI
  • Python/LangGraph
  • Ollama
  • Milvus
  • PostgreSQL
  • Redis
Computer Vision
Keywords:
  • Automotives
  • SLAM
  • PyTorch
  • OpenCV
  • FPGA
UI/UX
Keywords:
  • Slackbot
  • Python/FastUI
  • Open WebUI
  • Vercel AI SDK
  • .NET/MAUI
  • .NET/WPF
  • Unity
Programming languages
Keywords:
  • Python
  • .NET/C#
  • C/C++
  • MATLAB

Certifications

(Expired in )

🐳 KCSA: Kubernetes and Cloud Native Security Associate from The Linux Foundation

(Expired in )

🐳 KCNA: Kubernetes and Cloud Native Associate from The Linux Foundation

(Expired in )

🐙 CAPA: Certified Argo Project Associate from The Linux Foundation

(Expired in )

🐳 CKAD: Certified Kubernetes Application Developer from The Linux Foundation

(Expired in )

🐳 CKA: Certified Kubernetes Administrator from The Linux Foundation

Interests

Research/Dev
Keywords:
  • Agentic RAG
  • Digital Twins
  • AMD-to-ARM Transition
  • Hybrid Clusters
  • Home Clusters
DevOps Culture
Keywords:
  • Coop First, Tech Next
  • Automate as Possible
  • Internal Development Platform

Languages

  • Korean: Fluency: Native
  • English: Fluency: Working Proficiency