Job Description

Overview

We are seeking a highly skilled HPC/AI/ML Cluster Engineer to support the design, deployment, and ongoing operations of large-scale HPC environments powered by Slurm. This role centers on cluster engineering, administration, and performance optimization, with emphasis on GPU-accelerated computing, advanced networking, and workload scheduling. In this role, you will work closely with our researchers, vendors, and partners to manage Slurm clusters that are used for AI/ML workloads.

Responsibilities

Cluster Engineering & Deployment

• Participate in the design and bring-up of bare metal HPC/AI/ML environments
• Architect compute node definitions (NUMA, GRES GPU topologies, CPU pinning) and Slurm partitioning strategies for diverse workloads.
• Integrate heterogeneous hardware platforms into cohesive scheduling environments.
• Develop provisioning and imaging workflows (Ansible, MAAS, cloud-init, CI/CD pipelines) for reproducible cluster build-out.
• Coordinate communications between vendors, researchers, and other partners during cluster bring-up and operation.

Slurm Management

• Configure and operate the Slurm Workload Manager.
• Build custom Slurm plugins and scripts (epilog/prolog, pam_slurm_adopt) to extend functionality and integrate with authentication, and monitoring.
• Manage federated Slurm setups across multi-site or hybrid cloud environments.

System Administration & Monitoring

• Administer Linux HPC environments, including network configuration, storage integration, and kernel tuning for HPC workloads.
• Deploy and maintain observability stacks for system health, GPU metrics, and job monitoring.
• Automate failure detection, node health checks, and job cleanup to ensure high uptime and reliability.
• Manage security and access control (LDAP/SSSD, VPN, PAM, SSH session auditing).

User & Stakeholder Support

• Assist cluster users with developing workflows that make efficient use of compute resources.
• Containerize HPC applications with Docker/Podman/Enroot-Pyxis and integrate GPU-aware runtimes into Slurm jobs.
• Automate cost accounting and cluster usage reporting.

Qualifications

• 7+ years experience in HPC cluster administration and engineering, with deep knowledge of Slurm.
• Familiarity with common AI/ML software package dependencies and workflows
• Expert in Slurm configuration, partition design, QoS/preemption policies, and GRES GPU scheduling.
• Strong background in Linux system administration, networking, and performance tuning for HPC environments.
• Hands-on experience with parallel file system, advanced networking (InfiniBand, RoCE, 100/200 GbE), and monitoring stacks.
• Proficient with automation tools (Ansible, Terraform, CI/CD pipelines) and version control.
• Demonstrated ability to operate GPU-accelerated clusters at scale.

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