ML engineer (ML Platform / ML Serving / MLOps tracks) at Toss in Seoul, building the shared end-to-end ML pipeline — feature store, training, registry, inference, monitoring — plus GPU-based large-scale model serving and Kubernetes infrastructure. Key stack: TensorFlow Serving, TorchServe, Triton, TensorRT, Kubernetes, Docker, Kotlin/Spring Boot.