Join NVIDIA's high-performance computing infrastructure team as a Senior Slurm Administrator. You will play a pivotal role in designing, evaluating, and optimizing the compute resources that power NVIDIA's cutting-edge silicon design and AI workloads. This is an opportunity to own the Slurm environment within our VLSI compute domain and extend your expertise to the broader scheduling ecosystem.

This senior position offers a hands-on technical challenge, focusing on the core operational aspects of our compute infrastructure. You'll be instrumental in ensuring the smooth functioning and efficiency of our cluster operations, directly supporting our design engineers.

As the Slurm Administrator, you will be responsible for the comprehensive management, configuration, and tuning of Slurm clusters, including partitions, QOS, accounting, and node states. You will collaborate with existing LSF environments and drive automation for critical scheduler operations such as node onboarding, configuration management, and routine maintenance.

Key duties include developing and maintaining dashboards for performance monitoring, tracking job throughput, queue wait times, and SLA attainment. This role requires active engagement in cluster operations, supporting design engineers during business hours, and proactive job triage for daily operations.

We are seeking candidates with a B.E./B.Tech/M.Tech in Computer Science, Electrical Engineering, or equivalent experience, coupled with over 5 years of compute infrastructure experience, specifically managing batch scheduling systems.

A strong practical understanding of Slurm, including configuration, partitions, QOS, slurmdbd accounting, node management, and troubleshooting production job failures, is essential. Familiarity with a secondary scheduler like LSF, or a demonstrated ability to learn quickly, is highly desirable.

Proficiency in Linux system administration, including filesystems, NFS, networking, and resource management, is required. You should possess robust automation skills in Python and shell scripting, along with experience in monitoring and dashboarding tools. Comfort with operational load and production support is expected.