Senior HPC AI Engineer

NVIDIA

. Manage, scale, and optimize job scheduling systems such as LSF and Slurm in a large-scale, multi-site environment supporting EDA and compute-intensive workloads .

Posted 10/22/2026full-timeTel Aviv • IsraelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing and optimizing job scheduling systems like LSF and Slurm within large-scale Linux-based compute infrastructures. Proficient in automation, performance analysis, and implementing reliability engineering practices to enhance operational efficiency.

Highest-signal resume keywords

Job Scheduling Systems ManagementLinux Systems AdministrationPython ProgrammingCI/CD TechniquesReliability Engineering Practices

ATS Keywords

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Hard Skills

Job Scheduling SystemsLinux AdministrationPython ProgrammingBash ScriptingCI/CDInfrastructure as CodePerformance AnalysisAutomation ScriptingRoot Cause AnalysisAdvanced Troubleshooting

Soft Skills

Problem SolvingCollaborationCommunication

Tools & Technologies

LSFSlurmCentOSRHELDockerSingularityPodmanFLEXlmMonitoring PipelinesPerformance Dashboards

Industry Keywords

HPCEDACompute-Intensive WorkloadsObservability SystemsMetrics Collection

Tech Stack

Tools & technologies

DockerLinuxPython

About the role

Key responsibilities & impact

Manage, scale, and optimize job scheduling systems such as LSF and Slurm in a large-scale, multi-site environment supporting EDA and compute-intensive workloads
Analyze scheduler and infrastructure performance data to identify systemic bottlenecks and improve utilization, throughput, and turnaround time
Build and improve the ecosystem around GPU-accelerated computing
Define and develop automation scripts and wrapper tools for the IC Design environment
Identify recurring operational challenges and implement automation or process improvements to reduce manual effort and prevent repeat incidents
Perform root cause analysis and suggest corrective actions
Partner with customer teams to clarify requirements, translate technical tradeoffs, and drive issues to closure

Requirements

What you’ll need

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
Experience developing, fine-tuning, and deploying advanced LLM-based solutions
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)
Proficiency in modern CI/CD techniques, GitOps, and Infrastructure as Code (IaC)
Proficiency in Python programming and Bash scripting
Deep knowledge of job scheduling systems configuration tuning, scheduler internals, and advanced troubleshooting techniques
Experience with network licenses such as FLEXlm, including maintenance, provisioning, automation, monitoring, and troubleshooting
Experience implementing reliability engineering practices within HPC scheduling environments
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