Network Simulation Engineer

About Eridu Eridu is a Silicon Valley-based hardware startup pioneering infrastructure solutions that accelerate AI data centers to deliver Faster AI . Today’s AI performance is frequently limited by communication bottlenecks. Eridu introduces multiple industry-first innovations across silicon, packaging, software, and systems to deliver an order of magnitude improvement in performance and unlock greater GPU utilization to speed training job completion times and tokens-per-second for more profitable inference. We do this while simultaneously reducing capital and power costs and improving reliability. The company’s solutions and value proposition have been widely validated by leading hyperscalers. Eridu has raised over $200M to date including its most recent, oversubscribed Series A round. The company is led by a veteran team of Silicon Valley executives who have delivered multiple billion dollar product lines and led multiple companies to billion dollar exits, including serial entrepreneur Drew Perkins, co-founder of Infinera (NASDAQ: INFN), Lightera (acq. by Ciena), Gainspeed (acq. by Nokia) and Mojo Vision (the world’s leading micro-LED company). The company is in execution mode and has a world-class engineering team with decades of experience in state-of-the-art silicon, packaging, optics, software, and systems. Eridu is working with best-in-class supply chain partners including silicon, packaging and systems. Visit our website eridu.ai to learn more. Position Overview We are seeking a highly motivated Network Simulation Engineer to lead the simulation and analysis of AI communication workloads (e.g. collective communications) across various data center network topologies. In this role, you will apply network simulation tools to model real-world AI applications—including LLMs and DLRMs—to inform architectural decisions across Eridu’s product development lifecycle and to showcase our value to prospective customers and investors. You will collaborate cross-functionally with customers, ASIC designers, and simulation tool providers to optimize performance, influence design, and deliver transformative AI networking solutions. Responsibilities Model AI Workloads: Simulate communication patterns of distributed AI workloads (e.g., LLMs, DLRMs) across diverse network topologies to analyze performance and scalability. Drive Architecture Optimization: Work with customers to evaluate their AI workloads and provide recommendations for topology design, protocol tuning, and system architecture. Influence ASIC Design: Collaborate with the internal ASIC and architecture teams by providing simulation-based insights that shape chip design for optimized AI traffic flows. Tool Development & Partnership: Interface with simulation tool providers (who have optimized versions of NS-3, ASTRA-sim, etc.) to customize, tune, and enhance modeling frameworks for Eridu’s specific requirements and to operate these tools to run simulations. Documentation & Communication: Create clear and compelling reports, documentation, and presentations to communicate insights to technical and non-technical stakeholders. Qualifications MSc or PhD in Computer Science, Electrical Engineering, or a related field with some specialization in AI/ML communications or equivalent hands-on experience Strong experience with network simulation tools such as NS3, OMNeT++, or custom-built simulators. Familiarity with distributed training frameworks (e.g., PyTorch, TensorFlow), collective communication libraries (e.g., NCCL, RCCL), and GPU programming (CUDA or ROCm). Deep understanding of frontier model architectures, parallelism approaches and operational functionality Deep understanding of Ethernet, InfiniBand, and high-performance data center networking technologies. Solid grasp of AI system architecture, including compute, memory, and interconnect bottlenecks in large-scale training/inference clusters. Strong programming skills in C++ and Python. Clear and confident communication s