ML Accelerator Performance Validation Engineer, Post Silicon Validation

Job description

Annapurna Labs, an AWS organization with development centers in the U.S. and Israel, builds custom silicon and software for AWS customers. Our team combines cloud-scale innovation with world-class expertise across silicon engineering, hardware design, verification, software, and operations to tackle technical challenges that have never been seen before. Join our Post-Silicon Validation team to quantify and qualify the performance of AWS's custom ML training chips against architectural targets. You'll bridge the gap between silicon capabilities and real-world ML workload demands — ensuring our accelerators deliver on latency, throughput, and efficiency promises at cloud scale. You'll work in a fast-paced, startup-like environment alongside some of the brightest minds in the industry on next generation AI/ML hardware that powers AWS's training and inference infrastructure. Your analysis will directly shape architectural decisions for next-generation accelerators and determine when silicon is ready for production deployment. Key job responsibilities Design and execute performance benchmarks spanning micro-architectures to full model training Measure and analyze compute throughput, memory bandwidth, interconnect latency, and more Profile real ML workloads (transformer models, LLMs, vision models) on silicon Identify performance bottlenecks and work with architecture teams on optimization Build automated performance regression dashboards and tracking infrastructure Correlate silicon measurements against RTL…