[Remote] Senior HPC and LSF Operations Engineer - EDA Infrastructure

Note: The job is a remote job and is open to candidates in USA. NVIDIA is seeking a Senior HPC and LSF Operations Engineer for its Hardware Infrastructure EDA Compute team. The role supports and optimizes workload scheduling systems, resolves service-impacting issues, and advances automation, observability, reliability, and resource management across the EDA compute environment.

Responsibilities

• Manage, scale, and optimize job scheduling systems (LSF, Slurm, etc.) in a large-scale, multi-site environment supporting EDA and other compute-intensive workloads
• Analyze scheduler and infrastructure performance data to identify systemic bottlenecks and drive measurable improvements in utilization, throughput, and turnaround time
• Lead problem solving across scheduler, OS, and workload layers, ensuring timely resolution of service-impacting issues
• Identify recurring operational challenges and implement targeted automation or process improvements to reduce manual effort and prevent repeat incidents
• Help define and track reliable metrics and SLOs for service performance and reliability, partnering with customers to ensure expectations are realistic and measurable
• Contribute to operational standards, documentation, and best practices to improve consistency across sites
• Partner directly with customer teams to clarify requirements, translate technical tradeoffs, and drive issues to closure

Skills

• Bachelor's degree in Computer Science or related field, or equivalent experience
• Minimum 5+ years of experience operating and supporting large-scale Linux-based compute infrastructure
• Strong hands-on experience supporting and tuning job scheduling systems (LSF, Slurm, etc.) in HPC or silicon design environments
• Proficiency in Linux systems administration (CentOS/RHEL)
• Strong problem solving skills and the ability to independently analyze complex system behavior under load
• Clear and effective communication skills, including the ability to articulate technical tradeoffs and reliability metrics to engineering stakeholders
• Experience implementing reliability engineering practices within HPC scheduling environments
• Deep knowledge of job scheduling systems (LSF, Slurm, etc.) configuration tuning, scheduler internals, and advanced troubleshooting techniques
• Experience building or enhancing observability systems, including metrics collection, monitoring pipelines, alerting strategies, and performance dashboards
• Background with container technologies such as Docker, Singularity, or Podman in HPC environments
• Experience influencing adoption of new infrastructure standards across multiple teams or sites

Benefits

• Equity
• Hybrid work arrangement

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