Summary: Seeking a Senior DevOps Engineer to build and administer stable, scalable GPU compute platforms on Kubernetes and Linux for advanced AI and research initiatives. Highlights: 1. Design and maintain GPU-enabled Kubernetes clusters for optimal scheduling 2. Implement Python and Shell automation for streamlined operations 3. Optimize scheduling efficiency, capacity utilization, and researcher workflows We are creating stable, scalable GPU compute platforms on Kubernetes and Linux for advanced AI and research initiatives. As a Senior DevOps Engineer, you will administer Kubernetes, run Volcano scheduling, automate with Python and UNIX shell scripting, and help optimize capacity and observability for client delivery. Apply now and help improve researcher workflows **Responsibilities** * Design and maintain GPU-enabled Kubernetes clusters and standalone Linux compute environments to ensure optimal scheduling and throughput * Configure and manage Volcano scheduling, covering queue setup, POD execution, GPU allocation, and namespace quota enforcement * Administer Kubernetes environments end-to-end, including namespaces, RBAC, resource quotas, and workload isolation strategies * Implement Python and Shell automation to streamline job submission, resource provisioning, and system reporting * Coordinate with orchestration, optimization, and observability teams to improve scheduling efficiency, capacity utilization, and researcher workflows * Monitor infrastructure health and resource utilization, providing data that supports optimization and reporting requirements * Propose and implement improvements to infrastructure, tooling, and automation workflows to enhance performance, scalability, and usability * Maintain operational processes that deliver a seamless experience for researchers across AI and computational workloads **Requirements** * Minimum 3 years of experience in DevOps or infrastructure engineering roles supporting complex, large-scale environments * Expert knowledge of Kubernetes administration and orchestration, including namespaces, POD scheduling/distribution, PVC, NFS, and resource quota management * Hands-on experience with the Volcano scheduler for GPU job execution, queue configuration, workload prioritization, and Kubernetes integration * Proven experience managing GPU cluster environments in Kubernetes and on standalone Linux compute nodes * Advanced Python scripting expertise for infrastructure automation and proficiency in UNIX Shell scripting (e.g., Bash) * Strong Linux system administration skills, including troubleshooting, performance tuning, and configuration management * Solid understanding of infrastructure automation and orchestration concepts and associated tooling * Fluent English communication skills (spoken and written) for direct client interaction **Nice to have** * Helm skills for Kubernetes application packaging * Monitoring and observability experience, especially Prometheus, Grafana, and Loki * Terraform or similar Infrastructure as Code tooling * Multi-cloud Kubernetes experience (Amazon EKS, Google GKE) * Azure Networking experience with VPN, ExpressRoute, and network security * Familiarity with AI-assisted coding tools (e.g., GitHub Copilot, ChatGPT, Claude) * Hybrid (cloud + on-premises) scheduling and resource optimization experience