GPU Cloud Platform Engineer
Y
Yotta LabsAI Infrastructure
United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- 3+ years
- Required Skills
- AWSDockerPythonSQLBashCloud ComputingGCPGitKubernetesAzureGrafanagRPCPrometheusCI/CDRESTful APIsLinuxDevOpsTerraformJSONAnsibleNetworking
Requirements
- 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.
Responsibilities
- 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.
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