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About Hyunwoo Kim (Hans)

If you are intereted in me, you can get more detail about me by visiting my Portfolio page for detail!!

👉 Notion Portfolio 👈

(Notion Portfolio(Korean))


CONTACT INFORMATION

📮 Contacts

📚 Blog

🔗 SNS

I’m a software engineer who is curious about every new things. And “Keep Blitz and Be Simple”, “Keep It Simple Stupid” is my motto. I always try to be simple. 😊

🌥 SOFTWARE ENGINEER

Proficient in end-to-end planning and operation of MLOps platform as a Software Engineer

Skilled DevOps Engineer well-versed in Cloud Native technologies

Experienced System Engineer with expertise in operating large-scale HPC clusters, managing over 2000 GPUs

INTERESTS

🏢 WORK EXPERIENCES

Toss Bank

Machine Learning Software Engineer, Machine Learning Platform Team

Oct 2023 ~ Present

  • Built Machine Learning Platform, contributing to flexible model development and deployment.
  • Pioneered a high-performance Online Feature Store Platform leveraging ScyllaDB (Cassandra-compatible, high-performance NoSQL DB), achieving performance improvement in write throughput and read latency. Developed a Spring-based feature store API server to ensure low-latency feature access at scale.
  • Engineered and sustained a large-scale Airflow batch system managing 2K+ workflows across 7+ clusters, achieving 99.9% system uptime in the critical banking environment while optimizing DAG management to reduce batch processing time by 20%.
  • Contributed the operation of an AWS-based research network, boosting productivity by reducing research time by 50% with fortified data security measures.
  • Built a caching system using MongoDB, reducing errors by 60% within the credit scoring system, directly improving loan execution and driving revenue growth.
  • Migrated a data ingestion pipeline processing 9M+ daily records from Elasticsearch to MongoDB, enhancing data security and compliance, which contributed to reliable and scalable data handling.
  • Developed Python-based Credit Strategy System that cut deployment time by 50%, reduced costs and errors through automation, and enhanced credit decisions using Machine Learning models

Kakao Enterprise

Software Engineer, Machine Learning Platform Part

Mar 2022 ~ Aug 2023

Built large-scale MLOps platform that can manage the entire process from “Traning” to “Inference” and production model deployment.

  • Developed and maintained the Kakao i Machine Learning MLOps platform leveraging Golang and Python. Managed over 2,000 GPUs(NVIDIA A100, V100, T4) across 20+ Kubernetes clusters using Kubespray. Ensured smooth platform operation for approximately 200+ active users, achieving 99.9% system uptime.
  • Successfully operated a stable HPC(High-Performance Computing) cluster basede on Infiniband network. Also established and maintained stable infrastructure for high-performance computing projects in public environments.
  • Planned and executed the successful relocation of over 300 GPU, CPU devices for a major power facility relocation with 99.99% system uptime.

  • Developed MSA components in the backend (API Server), client (CLI, SDK) and infra element development of inference function for MLOps platform. And also built CI/CD system for platform over Kubernetes.

  • Developed managed Jupyter Notebook functionality for the MLOps platform by integrating open-source components such as JupyterHub and Enterprise Gateway, enabling users to launch notebooks with dynamically changeable kernel instance types.
  • Implemented Model Artifact resource functionality for the MLOps platform, including CRUD APIs, metadata support for model versioning, and tagging capabilities to enhance model traceability and management.
  • Established a unified API server error code policy by aligning multiple backend teams, facilitating clearer communication across engineering, frontend, and planning teams.
  • Led GPU migration and service continuity planning for the Kakao i Machine Learning platform, including the relocation of 200+ high-performance GPU devices. Collaborated cross-functionally to ensure seamless integration into Kubernetes clusters and maintained inference service stability during NAS and infrastructure transitions.

Software System Engineer, AI Lab Voice System Part

Jul 2020 ~ Feb 2022

Collaborated within the AI Lab, building infrastructure and tools to support voice-related research in an organization of 100+ AI researchers.

  • Designed and operationalized the Voice Transcription Tool with React and Django(Python), enabling 10+ transcribers to process 3K+ voice data daily, significantly enhancing transcription productivity and addressing domain drift issues in STT(Speech-to-Text).
  • Operated a Kakao i voice data log management system to handle 3M+ daily data logs from 100k+ users. Ensured data security by isolating sensitive voice data in secure zones, and streamlined data refinement to support transcription workflows and researcher access.
  • Built and operated the Kakao i Cloud STT service, enabling 20+ custom user language models on Kubernetes through a Python-based controller, resulting in efficient deployment and stable operation.
  • Developed real-time STT demo services with WebSocket streaming and file upload support to showcase Kakao i’s speech recognition features.

🛠 SKILLS

Language

  • Python
  • Go
  • Javascript

Cloud Native

  • Kubernetes
  • Docker
  • ArgoCD
  • Kubeflow

DevOps

  • ArgoCD
  • Github Action
  • Jenkins
  • Helm

Keywords

  • Microservice architecture
  • Linux/System programming
  • Machine Learning

📜 CERTIFICATIONS

AWS Certified Cloud Practitioner (CLF)

Issued Apr 2023 · Expires Apr 2026

MLOps Engineering on AWSMLOps Engineering on AWS

Issued Apr 2022 · Expires Apr 2025

🎓 EDUCATION

Kyungpook National University

2015.03 ~ 2021.02.

  • Bachelor of Computer Science
  • GPA : 4.10 / 4.50

Darmstadt Univ of Applied Sciences, Germany

Spring Semester 2020

  • International Studies Program
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