Senior HPCLM Optimization Engineer
On-site · Bengaluru, Karnataka, India or Hyderabad, Telangana, India
Job Summary
Senior HPCLM Optimization Engineer at Analog Devices (ADI) within the Engineering Enablement team. Responsibilities include analyzing cluster, queue, workload, and license telemetry to identify optimization opportunities; driving scheduler and policy tuning for job placement, queue design, fairshare behavior, right-sizing, and license-aware execution; profiling critical EDA and HPC workloads to improve CPU/GPU utilization, memory, I/O, and scaling; partnering with IT, Cloud, and workflow owners to resolve systemic issues; developing dashboards and KPIs for queue health, compute/license utilization, capacity forecasting, and cost optimization; applying automation and AI/ML-driven approaches for anomaly detection and congestion avoidance; documenting best practices and repeatable methods to improve resilience; and potentially aligning to Senior Engineer or Staff Analyst levels based on profile. The role emphasizes data-driven recommendations, cross-functional collaboration, and driving measurable improvements in throughput and user experience.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Electronics, Data Engineering, or a related technical field
- Strong experience in HPC environments, batch schedulers (LSF/Slurm/PBS etc), 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
- Ability to translate operational data into recommendations, influence cross-functional stakeholders, and drive actions to closure
- Strong communication skills with the ability to work effectively across engineering, support, workflow, and infrastructure teams
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