• Formulate benchmarking methods for high-performance computing and AI tasks. • Perform and bring these methods to completion on large-scale GPU clusters. • Assess performance metrics to detect optimization opportunities and upgrade architecture. • Develop and maintain telemetry infrastructure to capture performance data. • Collaborate closely with hardware engineering, software development, and customer-facing teams to define performance requirements, fix bottlenecks, and validate configurations against real-world workloads. • Deploy and manage observability stacks including monitoring tools like Prometheus, visualization platforms such as Grafana, NVIDIA's DCGM, and custom telemetry solutions to provide actionable insights into cluster health, utilization, and performance trends. • Work directly with engineering and collaborate with internal partners to understand their performance requirements, conduct on-site benchmarking engagements, and deliver detailed analysis and recommendations for workload optimization. • Maintain extensive knowledge of industry-standard benchmarks in advanced computing and machine learning fields such as HPL, HPCG, MLPerf, and NCCL tests. • Contribute to developing new benchmarking methodologies for emerging workloads.