Summary: Join a client-facing team as a Middle DevOps Engineer to enhance and administer Kubernetes and Linux platforms, focusing on GPU scheduling and automation for advanced AI workloads. Highlights: 1. Run and improve Kubernetes environments with a focus on GPU scheduling 2. Implement and administer Volcano for GPU job scheduling and optimization 3. Develop automation using Python and Shell scripting We are building dependable Kubernetes and Linux platforms, with a focus on GPU scheduling and automation at scale. As a **Middle DevOps Engineer**, you will run and improve Kubernetes environments (including Volcano) and the underlying Linux infrastructure using Python and Shell scripting in a client\-facing delivery team. Apply to help deliver efficient, reliable compute environments for advanced AI workloads. **Responsibilities** * Deploy, configure, and operate GPU\-enabled Kubernetes clusters and standalone Linux compute environments to keep scheduling and performance optimized * Implement and administer Volcano job scheduling, including queue setup, POD execution, GPU allocation, and namespace quota enforcement * Administer Kubernetes end to end, covering namespaces, RBAC, resource quotas, and workload isolation approaches * Create and maintain Python and Shell automation to simplify job submission, resource provisioning, and system reporting * Collaborate with orchestration, optimization, and observability teams to raise scheduling efficiency, improve capacity utilization, and streamline researcher workflows * Monitor infrastructure health and resource utilization, supplying data and feedback for optimization and reporting needs * Identify opportunities to enhance infrastructure, tooling, and automation workflows to improve performance, scalability, and usability * Ensure operational processes provide 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