We use PostHog and Clarity to improve the site, and Meta Pixel to measure page views and ad effectiveness. Usage data may include page addresses and browser identifiers. You can opt out of collection at any time. Details in the Privacy Policy
Senior Technical Support Engineer – Slurm at Nvidia · Trevo
NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for over 30 years. It's a unique legacy of innovation fueled by great technology—and dynamic people. Today, we're tapping into the unlimited potential of AI to define the next era of computing—an era in which our GPUs act as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. NVIDIANs immerse themselves in a diverse, supportive environment that encourages everyone to do their best work. Join the team and see how you can make a lasting impact on the world. Slurm is a critical workload manager for many of the world's most demanding AI and high-performance computing environments.
We are looking for a Technical Support Engineer dedicated to supporting Slurm for NVIDIA's customers. You will join a dedicated team of Slurm subject-matter guides, owning sophisticated support cases and helping customers run reliable, efficient, and highly scalable clusters. This role requires extensive production experience with Slurm and the ability to diagnose issues across the scheduler and the surrounding Linux, networking, storage, authentication, database, and GPU infrastructure.
What you'll do
Own Slurm support cases from initial investigation through resolution for customers running production AI and HPC clusters.
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.c degree in Computer Science, Engineering, or a related field, or equivalent 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.