Power & Performance Engineer (AI)

TL;DR

Power & Performance Engineer (AI): Developing and optimizing power and performance metrics for large-scale AI data center hardware with an accent on silicon-to-pod level telemetry and thermal management. Focus on building workload characterization pipelines, driving dynamic power management strategies, and ensuring efficiency within strict power envelopes.

Location: Must be based in Israel (Haifa or Petah-Tikva). This role follows a hybrid work model requiring on-site presence at hirify.global facilities.

Company

A global leader in semiconductor design and manufacturing, driving innovation in AI hardware and computing solutions.

What you will do

• Own pod-level power and performance metrics for large-scale AI data centers using advanced modeling platforms.
• Aggregate silicon and rack data to reconcile measured versus modeled performance and manage power budgets.
• Drive power telemetry and dynamic management techniques including RAPL, P/C-states, and DVFS to maximize throughput.
• Build and maintain workload characterization and benchmarking pipelines for SPEC, MLPerf, and AI workloads.
• Collaborate with facilities and electrical teams on power distribution, PUE targets, and peak-demand management.
• Provide feedback to partner teams to improve the accuracy and coverage of telemetry and modeling tools.

Requirements

• Bachelor's, Master's, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• 5+ years of professional experience in power, performance, or systems optimization.
• Deep technical knowledge of CPU/GPU power management, performance counters, and Linux power frameworks.
• Proficiency in data analysis using Python and SQL.
• Must be eligible to work in Israel and available for hybrid on-site work.

Nice to have

• Experience with PUE and thermal modeling.
• Background in pod-level capacity planning.
• Familiarity with AI cluster scaling challenges.

Culture & Benefits

• Opportunity to work in a startup-like, agile environment within a major corporation.
• Access to cutting-edge AI hardware development and modern chip design methodologies.
• Hybrid work flexibility balancing on-site collaboration with off-site work.
• Exposure to large-scale data center infrastructure and high-impact technical challenges.