CakeResume 找人才

Deploy On-Premise Kubernetes cluster and operation tasks like monitoring, scaling up/down nodes, troubleshooting, and root cause analysis Designed and built ML platform core features, like model management, advanced deployment strategy, event-drive automation workflow De-dependency ML pipelines(MLOps) and leverage GitOps for continuous deployment supported 10+ machine learning services, accumulated 20 million+ API requests since theplatform launched, and 99.9% Monthly Uptime Percentage SLA smart recommendation service Resolving data scientist requirement Kubernetes/ golang /spark/airflow Introduces spark-operator solution for big data ETL in airflow k8s executor Design and implement

楊閔翔 2013年畢業於中興大學研究所之後,主要經歷皆致力於以人工智慧進行影像辨識相關之演算法開發,從最早期的descriptor + machine learning,到這幾年開始使用deep learning,工作中經歷學界和業界的轉換,因此能同時掌握最新技術,並在實務上使用並取得成果 TW