Sandisk is hiring a HPC Engineer

Role Overview Experienced Senior HPC Engineer / Architect specializing in Linux-based high-performance computing (HPC) environments, EDA workflows, and automation-driven infrastructure. Proven expertise in designing, managing, and optimising large-scale distributed HPC clusters supporting ASIC EDA workloads. Key Responsibilities Architect, deploy, and manage large-scale distributed HPC environments across global locations, supporting ASIC and GPU compute clusters Design and implement infrastructure automation using Ansible, Shell, and Python for system lifecycle management Administer and optimize workload schedulers (LSF, Slurm, NC) including queue configuration, fair-share policies, and job prioritization Perform deep troubleshooting and root cause analysis across compute, storage, networking, and scheduler layers Collaborate with engineering teams to improve EDA workload performance and efficiency in global HPC environments Develop and deploy self-service automation solutions to reduce manual effort and improve system reliability Manage and support EDA ecosystem including tool deployment (Cadence, Synopsys), licensing, and workflow optimization Implement monitoring & observability frameworks using tools like Splunk, Grafana for proactive issue detection Drive capacity planning, performance tuning, and resource optimization for HPC workloads Create and maintain technical documentation, runbooks, and operational standards Provide technical leadership and mentoring, influencing HPC architecture and long-term strategy Techncal Skills HPC & Scheduling: LSF, Slurm, Network Computer (NC), Grid/Batch scheduling Operating Systems: RedHat Enterprise Linux (RHEL), CentOS Automation & Scripting: Ansible, Shell/Bash, Python EDA Tools: Cadence, Synopsys, EDA workflows & design environments Monitoring & Observability: Splunk, Grafana, Prometheus Storage & Filesystems: NFS, AutoFS, distributed storage systems Authentication & Access: UNIX/Linux integrated with Active Directory Infrastructure: On-premises & Hybrid HPC environments Remote Access & VDI: Exceed TurboX, VNC, nomachine Preferred Skills Extensive experience with job schedulers such as LSF, Slurm, or equivalent platforms Experience supporting EDA / semiconductor design environments Exposure to GPU computing and accelerator-based workloads Knowledge of EDA licensing systems and optimization Experience with Infrastructure as Code (IaC) and platform standardization Familiarity with cloud or hybrid HPC architectures (AWS/Azure HPC)