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, unlock greater GPU utilization, and speed training job completion times and tokens‑per‑second for more profitable inference.

We also reduce capital and power costs while improving reliability.

The company’s solutions and value proposition have been widely validated by leading hyperscalers. Eridu has raised over $200 M to date, including an oversubscribed Series A round. The executive team consists of veterans who have delivered multiple billion‑dollar product lines and led companies to exits, including serial entrepreneur Drew Perkins, co‑founder of Infinera (NASDAQ: INFN), Lightera (acquired by Ciena), Gainspeed (acquired by Nokia) and Mojo Vision, the world’s leading micro‑LED company.

Eridu is in execution mode with a world‑class engineering team possessing decades of experience in state‑of‑the‑art silicon, packaging, optics, software, and systems. We work with best‑in‑class supply‑chain partners across all domains.

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 large‑language models (LLMs) and deep‑learning recommendation models (DLRMs)—and inform architectural decisions throughout Eridu’s product development lifecycle, showcasing 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.

• Model AI workloads:
  Simulate communication patterns of distributed AI workloads 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, customizing, tuning, and enhancing modeling frameworks for Eridu’s specific requirements and operating the tools to run simulations.
• Documentation & communication:
  Create clear and compelling reports, documentation, and presentations to communicate insights to technical and non‑technical stakeholders.

• MSc or PhD in Computer Science, Electrical Engineering, or a related field with specialization in AI/ML communications, or equivalent hands‑on experience.
• Strong experience with network simulation tools such as NS‑3, OMNeT++, or custom-built simulators.
• Familiarity with distributed training frameworks (e.g., PyTorch, Tensor Flow), 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 knowledge of Ethernet, Infini Band, 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.
• Proficiency in C++ and Python.
• Clear and confident communication skills, both written and verbal.
• 2+ years of relevant experience preferred; exceptional early‑career candidates will also be considered.

At Eridu, you’ll shape the future of AI infrastructure, working with a world‑class team on groundbreaking technology that pushes the boundaries of AI performance. Your contributions will directly impact the next generation of AI infrastructure solutions, transforming the performance of AI data centers.

The starting base salary for the selected candidate will be determined based on relevant skills, experience, qualifications, work location, market trends, and the compensation of employees in comparable roles.