Senior HPCLM Optimization Engineer

Responsibilities

• Analyze cluster, queue, workload, and license telemetry to identify optimization opportunities for throughput, fairness, and reliability.
• Drive scheduler and policy tuning for job placement, queue design, and license-aware execution.
• Profile critical EDA and HPC workloads to analyze CPU, GPU, memory, and I/O behavior to provide actionable tuning recommendations.
• Partner with Engineering Enablement, IT, and Cloud teams to resolve systemic issues and prevent repeat incidents.
• Develop dashboards and KPIs for queue health, capacity forecasting, and cost optimization.
• Apply automation and AI/ML-driven approaches for anomaly detection and proactive congestion avoidance.
• Document best practices and operational playbooks to improve system resilience.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Electronics, Data Engineering, or a related technical field.
• Strong experience in HPC environments and batch schedulers (e.g., LSF, Slurm, or PBS).
• Hands-on knowledge of Linux systems, scripting/automation, and troubleshooting distributed compute environments.
• Experience with workload profiling and resource optimization for compute and license-constrained environments.
• Experience driving GPU enablement, including GPU-aware scheduler configuration and resource allocation.
• Strong communication skills with the ability to influence cross-functional stakeholders.

Preferred Qualifications

• Experience with HyperScheduler or comparable enterprise job schedulers.
• Knowledge of EDA workload behavior and FlexLM/license management.
• Exposure to AWS or hybrid cloud scaling models and cost optimization.
• Working knowledge of AI/ML techniques for operational system optimization.
• Proficiency in building analytics pipelines using Python, SQL, or Grafana.
• Exposure to LLMs and AI-assisted automation for EDA workflows.

About the Company

Analog Devices, Inc. (ADI) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. We combine analog, digital, AI, and software technologies to drive advancements in automation, robotics, mobility, healthcare, and data centers.