Senior HPCLM Optimization Engineer

The HPCLM Optimization Engineer will work across Job Scheduler, EDA Workloads, HPC infrastructure, GPU Accelerators, cloud scale-out patterns, workflow behavior, and license operations to identify and implement improvements that increase throughput, reduce contention, and improve user experience. Depending on candidate profile and leveling, this role may be hired as a Senior Engineer or Staff Analyst.

Responsibilities and Duties include but are not limited to:

- Analyze cluster, queue, workload, and license telemetry to identify optimization opportunities across throughput, fairness, efficiency, and reliability.

- Drive scheduler and policy tuning for job placement, queue design, fairshare behavior, right-sizing, and license-aware execution.

- Profile critical EDA and HPC workloads to analyze CPU utilization, GPU acceleration characteristics, memory and I/O behavior, runtime performance, and scaling efficiency, and translate findings into actionable tuning and optimization recommendations.

- Partner with Engineering Enablement, IT, Cloud, workflow owners, and developers to resolve systemic issues and prevent repeat incidents.

- Develop dashboards, KPIs, and data-driven reporting for queue health, Compute/License utilization, capacity forecasting, and performance and cost optimization outcomes.





- Apply automation and AI/ML-driven approaches where appropriate for anomaly detection, demand forecasting, and proactive congestion avoidance.

- Document best practices, operational playbooks, and repeatable methods to improve resilience and reduce reliance on a small set of experts.

Required Qualifications

- Bachelor s or Master s degree in Computer Science, Electrical Engineering, Electronics, Data Engineering, or a related technical field.
- Robust experience in HPC environments, batch schedulers (LSF, Slurm, PBS), EDA compute workflows, GPU Enabled Infrastructure, or large-scale infrastructure operations.
- Hands-on knowledge of Linux systems, scripting/automation, telemetry analysis, and troubleshooting of distributed compute environments.
- Experience with workload profiling, performance analysis, or resource optimization for compute and license-constrained environments.
- Experience driving GPU porting and enablement including GPU-aware scheduler configuration and resource allocation policies.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Senior HPCLM Optimization Engineer (Hyderabad)
🏢 Analog Devices
📍 Hyderabad