GPU Cloud Platform Engineer

Bachelor's degree or higher in Computer Science, Software Engineering, Electronic Engineering, or related fields. 3+ years of experience in system engineering or DevOps. 5+ years of experience in cloud-native development or AI engineering. At least 2 years of hands-on experience in Kubernetes multi-cluster management and orchestration. Familiarity with the Kubernetes ecosystem, including kubectl and Helm. Proficient in Docker and containerization technologies. Experience with monitoring tools such as Prometheus and Grafana. Hands-on experience with cloud platforms such as AWS, GCP, or Azure.

Build and operate large-scale, high-performance GPU clusters. Conduct performance testing and evaluation of multi-node GPU clusters. Deploy and orchestrate large models across multi-cluster environments using Kubernetes. Participate in the design, development, and iteration of GPU cluster scheduling and optimization systems. Build a unified multi-cluster management and monitoring system. Coordinate with IDC providers for planning and deploying large-scale GPU clusters.