- MLOps Engineer — building cloud‑native ML infrastructure, GPU allocators & GitOps workflows for AI services.
- Designing distributed training & inference stack on Kubernetes/Kubeflow.
- Advocating IaC + observability across 50+ micro‑services.
| Period | Role | Highlights |
|---|---|---|
| 2023 → 2024 | Freelance DevOps Engineer | • Implemented enterprise SSO (SAML & OIDC) • Managed AWS CodePipeline / Terraform • Shipped Flask‑based backend APIs |
| 2024 → 2025 | HIGH PERFORMANCE COMPUTING RESEARCHER | • Doing Research at HPC Lab |
| Period | Institution | Program |
|---|---|---|
| 2020‑03 → 2023‑02 | Sejong University | B.S. Software Engineering |
| 2024‑08 → 2026‑05 (exp.) | USC | M.S. Computer Science |
| Domain | Stack |
|---|---|
| Languages |    |
| Backend |    |
| Frontend |    |
| DevOps / Infra |     |
| MLOps |    |
| Databases |    |
| Observability |   |
| Misc. |    |
| Project | Brief |
|---|---|
| Dynamic‑GPU‑Fraction | Runtime for fractionalizing GPU slots across pods; admission controller(HAMi + Kueue) + custom scheduler. |
| Hunger Detection | Experimenting with quantization/distillation to shrink the model for wearable devices.. |
| sso‑gateway | Plug‑and‑play SSO proxy supporting SAML / OAuth2 for legacy apps. |