Fabric Modeling and Analysis Engineer for Scale Up Fabric (2026-325)
Astera Labs (NASDAQ: ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera Labs’ Intelligent Connectivity Platform integrates CXL®, Ethernet, NVLink, PCIe®, and UALink™ semiconductor-based technologies with the company’s COSMOS software suite to unify diverse components into cohesive, flexible systems that deliver end-to-end scale-up, and scale-out connectivity. The company’s custom connectivity solutions business complements its standards-based portfolio, enabling customers to deploy tailored architectures to meet their unique infrastructure requirements. Discover more at www.asteralabs.com.Fabric Modeling and Analysis Engineer- Scale Up Fabric Role Overview Astera Labs is powering the connectivity behind rack-scale AI, and our Scorpio Scale-Up Fabric is central to how tomorrow’s GPU clusters scale. As a Fabric Modeling and Analysis Engineer, you will own the performance models that shape this fabric — quantifying bandwidth, latency, and throughput ceilings, and predicting how Scorpio hardware behaves under real AI/ML workloads long before silicon exists. This is a high-impact role for an engineer who thrives where architecture, performance analysis, and software converge. Your models will shape the next generate products and enable informed architectural decisions ahead of tape-out, surface bottlenecks that only appear at scale, and translate directly into roadmap and IP decisions. As Astera Labs continues its hyper-growth, you’ll be the internal authority on fabric modeling. Key Responsibilities Simulation Infrastructure & Model Correlation Design, implement, and maintain features in AI/ML system simulators and fabric models, extending support for collective communication, transport, topology, congestion, routing, buffering, scheduling, and traffic management Improve simulator fidelity, scalability, debuggability, and runtime performance across packet-level, flow-level, and analytical backends, and build reusable abstractions and APIs for end-to-end simulation flows Continuously calibrate and validate models against benchmark data from the Performance Engineering team, owning the correlation between model predictions and measured silicon across scale up fabric generations Analytical & Fabric Performance Modeling Design and implement transaction-level or cycle-approximate system models of the Scale up fabric, enabling rigorous evaluation of new architectural ideas early in the design cycle, well before tape-out Develop and own theoretical roofline and analytical models that establish bandwidth, latency, and throughput ceilings for the Scale-Up fabric, mapping AI/ML workload demands against fabric capabilities to identify compute-bound vs. fabric-bound regimes Model AI/ML collective commu...