Diagnose complex problems involving slurmctld, slurmd, slurmdbd, job scheduling, node management, resource allocation, accounting, authentication, and high availability.
Solve Slurm configuration and policy features, including partitions, reservations, priorities, fair-share, quality of service, backfill, preemption, GRES/TRES, cgroups, and job constraints.
Investigate performance, reliability, and scalability issues using logs, diagnostic data, configuration analysis, reproductions, and source-level debugging when required.
Isolate problems across Slurm and its surrounding dependencies, including Linux, MUNGE, databases, networking, parallel storage, containers, GPUs, and cluster-management systems.
Advise customers on Slurm configuration, upgrades, operational practices, managing system resources, and safe recovery from production incidents.
Collaborate with engineering teams by producing clear technical descriptions, reproducible test cases, and well-supported defect reports.
Develop guides, knowledge-base articles, diagnostic tools, and internal training that strengthen Slurm expertise across the support organization.
What we need to see
BS degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
5+ years of hands-on experience administering and supporting Slurm in production HPC or AI environments including business-critical outage incidents.
Expert-level understanding of Slurm architecture, daemons, configuration, scheduling behavior, accounting, resource management, and failure modes.
Capacity to identify sophisticated Slurm incidents independently and guide them to a technically sound resolution.
In-depth Linux system-administration and solve experience, including systemd, cgroups, authentication, networking, and database-backed services.
Experience operating Slurm across multi-user clusters with complex scheduling policies and heterogeneous compute resources.
Strong analytical and research skills, showing proficiency in distinguishing Slurm defects from configuration, integration, infrastructure, and workload problems.
Excellent written and verbal communication skills, including the ability to turn detailed technical findings into clear explanations and actionable recommendations.
Ways to stand out from the crowd
Experience supporting large-scale Slurm environments containing thousands of nodes or GPUs.
Experience diagnosing scheduler performance, job-throughput, controller-load, and database-scaling issues.
Familiarity with Slurm source code, plugins, SPANK, Lua job-submit plugins, or upstream issue investigation.
Experience with containers and HPC integration technologies such as Pyxis, Enroot, Apptainer, or Singularity.
Previous experience integrating Slurm with NVIDIA Base Command Manager, Bright Cluster Manager, or another cluster-management platform.
