Senior HPC AI Engineer
Salary not listed • Israel, Yokneam • Full-time
Posted 9d ago
About the job
As a member of the Hardware Infrastructure EDA Compute team, you will optimize, scale, and support workload scheduling systems that directly impact design velocity and infrastructure efficiency. You will combine deep scheduler expertise (LSF, Slurm) with automation, CI/CD, and LLM-based tooling to keep the EDA and GPU-accelerated AI compute environment resilient and measurable.
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.
- 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 targeted automation or process improvements to reduce manual effort and prevent repeat incidents.
- Perform root cause analysis and suggest corrective actions for problems of all scales.
- Partner directly with customer teams to clarify requirements, translate technical tradeoffs, and drive issues to closure.
Requirements
- 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.
- Develop, fine-tune, and deploy 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).
- Proficient in modern CI/CD techniques, GitOps and Infrastructure as Code (IaC).
- Proficient in Python programming and bash scripting.