Summary: Join a team operating Kubernetes and Linux GPU infrastructure to optimize AI compute performance and researcher experience through automation and reliable scheduling. Highlights: 1. Operate and tune GPU-enabled Kubernetes clusters for optimized performance 2. Build Python and Bash automation for job workflows and system reporting 3. Enhance infrastructure and tooling for performance, scalability, and usability We are operating Kubernetes and Linux GPU infrastructure that emphasizes Volcano\-based scheduling, reliability, and automation for AI compute at scale. As a Middle DevOps Engineer, you will administer Kubernetes and Linux environments, build Python and Bash automation for job workflows, and work closely with client stakeholders in a delivery team. Apply to help optimize compute performance and researcher experience for demanding AI workloads. **Responsibilities** * Operate and tune GPU\-enabled Kubernetes clusters and standalone Linux compute environments to keep scheduling and performance optimized * Manage Volcano job scheduling, including queue setup, POD execution, GPU allocation, and namespace quota enforcement * Administer Kubernetes end to end with namespaces, RBAC, resource quotas, and workload isolation approaches * Create and support Python and Shell automation to simplify job submission, resource provisioning, and system reporting * Work with orchestration, optimization, and observability teams to raise scheduling efficiency, improve capacity utilization, and streamline researcher workflows * Measure infrastructure health and resource utilization, supplying data and feedback for optimization and reporting needs * Enhance infrastructure, tooling, and automation workflows to improve performance, scalability, and usability * Ensure operations deliver a smooth and efficient experience for researchers running diverse AI and computational workloads **Requirements** * Hands\-on background with 2\+ years of experience in DevOps or infrastructure engineering within complex, large\-scale environments * Expertise in Kubernetes administration and orchestration, including namespaces, POD scheduling/distribution, PVC, NFS, and resource quota management * Practical experience with the Volcano scheduler for GPU job execution, queue configuration, and workload prioritization integrated with Kubernetes * Proven ability to operate GPU cluster environments in Kubernetes as well as on standalone Linux compute nodes * Advanced Python scripting skills for infrastructure automation, plus proficiency in UNIX Shell scripting such as Bash * Strong Linux system administration skills, including troubleshooting, performance tuning, and configuration management * Solid understanding of infrastructure automation and orchestration concepts and related tooling * Fluent English communication skills (spoken and written) for direct client interaction **Nice to have** * Knowledge of Helm package management for Kubernetes applications * Familiarity with monitoring and observability solutions, particularly Prometheus, Grafana, and Loki * Skills in Infrastructure as Code tools such as Terraform * Background in multi\-cloud Kubernetes environments including Amazon EKS and Google GKE * Understanding of Azure Networking including VPN, ExpressRoute, and network security * Familiarity with AI\-assisted coding tools such as GitHub Copilot, ChatGPT, and Claude * Experience with hybrid (cloud and on\-premises) scheduling and resource optimization