--- title: 'Network Systems Architect at Cerebras Systems' canonical: 'https://feeny.ai/job/network-systems-architect-cerebras-systems-sunnyvale-2k2y3zdma6bs' type: 'job' last_seen: '2026-09-22' --- # Network Systems Architect at Cerebras Systems - **Company:** [Cerebras Systems](https://feeny.ai/companies/cerebras-systems) - **Location:** Sunnyvale, CA - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-09-18 - **Last confirmed live:** 2026-09-22 - **Apply:** https://jobs.ashbyhq.com/cerebras/3b875977-293c-4277-bd04-55f34273c443 ## Job description Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. [OpenAI recently announced a multi-year partnership](https://openai.com/index/cerebras-partnership/) with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. ## About the Role As a Network Systems Architect, you will define the scale out, and particularly scale-up network architecture for current and future Cerebras platforms, including proprietary accelerator interconnects, protocols, and switching. Requirements will not arrive as a finished bandwidth and latency specification. Working with application, compiler, runtime, and systems teams, you will study communication patterns, workload partitioning and placement, data and memory movement, synchronization, locality, and failure behavior, then translate them into measurable fabric requirements. Your primary focus is low-latency scale-up and system fabrics, with enough breadth across scale-out and customer-facing networks to define clean boundaries. You will decide when standards-based or routable technology is right and when a simpler custom protocol or switching design produces a better system result. Hands-on here means that architectural judgment is grounded in prior low-level implementation, modeling, bring-up, or debugging. You will write specifications, guide models and prototypes, make technical decisions, and stay engaged through implementation and qualification. ## Responsibilities - Set the multi-generation architecture and roadmap for Cerebras scale-up networks and their interfaces to scale-out and customer-facing networks. - Work with application, compiler, runtime, and communication-library teams to understand mapping and communication choices, then derive the required bandwidth, latency, ordering, availability, and serviceability. - Define fabric topology, protocols, and switch behavior, including routing, buffering, flow control, reliability, and fault containment. Connect data-plane choices to end-to-end system behavior. - Decide when to use standards-based technology or merchant silicon and when a custom protocol, switch, link, or offload is justified. - Use performance models, traffic simulation, prototypes, and lab data to test architecture choices and set acceptance criteria. - Write architecture and interface specifications, lead design reviews, and drive cross-layer decisions through implementation, bring-up, and qualification. ## Qualifications - BS, MS, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. - Typically 12 or more years of relevant industry experience, including principal-level technical ownership of a major networking, switching, accelerator, or HPC system from architecture into implementation or deployment. - Deep expertise in low-latency or proprietary interconnects, fabric protocols, switch architecture, or a closely related area, with enough data-plane depth to reason about switch pipelines, buffering, routing, flow or congestion control, and reliability. - Experience deriving network requirements from incomplete workload and system information, with the range to make decisions across software, accelerator I/O, topology, and physical constraints. - Working knowledge of Ethernet, IP, and RDMA, plus conceptual familiarity with BGP and EVPN and the tradeoffs between routed networks and simpler low-latency scale-up designs. - Architectural judgment grounded in prior implementation, modeling, silicon, lab, bring-up, or debugging work. - A record of making clear technical decisions and influencing engineering leaders, implementation teams, suppliers, and customers. ## Preferred Experience Relevant experience may include one or more of the following. - Proprietary accelerator interconnects or scale-up technologies such as NVLink, xGMI, TPU ICI, Xe Link, or UALink-class systems. - Switch ASIC, NIC or DPU, accelerator I/O, transport offload, collective acceleration, coherent memory, or custom-fabric work. - FPGA architecture or mapping experience, or work with other placement-sensitive systems where topology materially affects communication. - AI or HPC communication stacks such as NCCL, RCCL, MPI, SHMEM, or proprietary collective libraries. - RoCE, InfiniBand, PCIe, CXL, or other relevant scale-out and I/O technologies. - Workload-driven modeling, traffic simulation, emulation, or pre-silicon and post-silicon correlation. - Working awareness of SerDes, packaging, retimers, cabling, optics, and reach constraints. ## Why Join Cerebras People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras: - Build a breakthrough AI platform beyond the constraints of the GPU. - Publish and open source their cutting-edge AI research. - Work on one of the fastest AI supercomputers in the world. - Enjoy job stability with startup vitality. - Our simple, non-corporate work culture that respects individual beliefs. Find out more about what it's like to work at Cerebras [here](https://www.cerebras.ai/join-us)! Apply today and become part of the forefront of groundbreaking advancements in AI! Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click [here](https://www.cerebras.net/privacy/) to review our CCPA disclosure notice. ## About Cerebras Systems ## Company Overview - **One-liner**: Cerebras builds wafer-scale AI chips (the largest semiconductors ever made) and supercomputers that deliver up to 15x faster inference than GPUs, offered both on-premises and via cloud APIs. - **Entity Type**: Public (NASDAQ: CBRS) — filed for IPO and now listed on the Nasdaq. - **Headquarters**: Sunnyvale, California, United States - **Founded**: 2015 - **Founders**: Andrew Feldman, Gary Lauterbach, Michael James, Sean Lie, Jean-Philippe Fricker ## Core Business - **Primary industries**: Semiconductor manufacturing, AI computing hardware and software, cloud AI services. - **Target customers**: B2B – enterprises, government research labs, cloud service providers, and AI developers. - **Mission**: “Building impossible technologies so you can too” – accelerating AI through wafer-scale computing. ## Products & Services - **Wafer-Scale Engine (WSE-3)**: The world’s largest AI chip (215 mm²), 58x larger than a typical GPU, built for ultra‑fast AI training and inference. Manufactured by TSMC. - **CS-3 Supercomputer**: A single system powered by the WSE-3, delivering record-breaking AI performance for on-premises deployment. - **Cerebras AI Inference Cloud & Training Cloud**: Pay-as-you‑go APIs that provide drop‑in OpenAI‑compatible access to Cerebras’ hardware for serving, fine‑tuning, and pre‑training models. - **Condor Galaxy Network**: A series of supercomputers (e.g., CG‑1 with 4 exaFLOPs) built in partnership with G42 for high‑performance AI. ## Market Standing - **Valuation/Market Cap**: Not disclosed (recently public; market cap data not available in provided sources). - **Key Metric**: Annual revenue of $78.7 M (latest); total funding of $2.7 B across 15 rounds. - **Notable Investors/Partners**: G42, OpenAI (signed in 2026), Amazon Web Services (signed in 2026), Meta (Llama API), Perplexity, Mistral, Hugging Face, OpenRouter. - **Growth Signals**: - 34.3% YoY headcount growth (701 employees). - Rapid data center expansion across North America and Europe. - Won the HPCwire Readers’ & Editors’ Choice 2025 for Best AI Product/Technology. - Named to Forbes America’s Best Startup Employers 2026 and Fast Company Most Innovative Companies 2026 (AI). ## Competitive Advantages - **Wafer‑scale architecture**: Eliminates interconnect bottlenecks, reducing latency and delivering up to 15x faster inference than GPU clusters. - **Largest AI chip ever built**: 58x larger than any GPU, enabling massive on‑chip memory (SRAM) and compute density. - **Full‑stack offering**: Hardware + cloud APIs + on‑prem systems, giving customers deployment flexibility. - **Strong customer relationships**: Key contracts with OpenAI, AWS, G42, and Mayo Clinic (2024 Gordon Bell Prize work). ## Strategic Focus - **Scale inference capacity**: Building out data centers to become the world’s #1 provider of high‑speed AI inference. - **Deepen cloud partnerships**: Expanding pay‑as‑you‑go cloud access and enterprise deployments. - **Advance wafer‑scale technology**: Continuous R&D on WSE‑3 successors and software stack (compiler, ML workflows). - **Broaden model support**: Already serving Llama, Gemma, Qwen, Mistral, and more; integrating with Hugging Face and OpenRouter. ## Why Work Here - **Culture**: “Extraordinary people, breakthrough innovation, global impact” – the company highlights collaborative, low‑overhead teams with little bureaucracy. - **Work environment**: Hybrid/office with locations in Sunnyvale, San Diego, Toronto, and Bangalore. Inclusive and flexible policy. - **Perks**: Premium medical/dental/vision, life insurance, generous vacation, 401(k) and Group RRSP retirement plans, daily catered meals, healthy snacks, family‑friendly events (including CEO’s famous BBQ). - **Engineering focus**: Tackling fundamental challenges in chip design, system software, compiler technology, and ML workflows. Positions range from hardware (Design Verification, Manufacturing) to software (SRE, Compiler, Cloud). - **Philanthrophy**: Supports local communities and hosts students from around the world for Q&A. ## Sources 1. [cerebras.ai/company](https://www.cerebras.ai/company) 2. [cerebras.ai](https://www.cerebras.ai/) 3. [cerebras.ai/join-us](https://www.cerebras.ai/join-us) 4. [linkedin.com/company/cerebras-systems](https://www.linkedin.com/company/cerebras-systems) ## Other roles at Cerebras Systems - [Senior Detection and Response Engineer](https://feeny.ai/job/senior-detection-and-response-engineer-cerebras-systems-sunnyvale-gx4sa9aschnm) — Sunnyvale, CA - [Staff Software Engineer, Inference API](https://feeny.ai/job/staff-software-engineer-inference-api-cerebras-systems-toronto-x8w1yn3zt3a6) — Toronto, Canada - [Staff AI Engineer – Business Systems](https://feeny.ai/job/staff-ai-engineer-business-systems-cerebras-systems-sunnyvale-vgybt0ehv5wt) — Sunnyvale, CA - [Senior ERP Systems Administrator](https://feeny.ai/job/senior-erp-systems-administrator-cerebras-systems-sunnyvale-z6p5ssmrtw01) — Sunnyvale, CA - [AI Datacenter Infra engineer](https://feeny.ai/job/ai-datacenter-infra-engineer-cerebras-systems-toronto-8kttfyzpb990) — Toronto, Canada - [Network Security Engineer (Remote)](https://feeny.ai/job/network-security-engineer-remote-cerebras-systems-united-states-yfrjb08d4wh9) — United States - [Distributed Systems Security Engineer](https://feeny.ai/job/distributed-systems-security-engineer-cerebras-systems-sunnyvale-01dxh99a668h) — Sunnyvale, CA - [Software Supply Chain Security Engineer](https://feeny.ai/job/software-supply-chain-security-engineer-cerebras-systems-sunnyvale-qct49y689pzb) — Sunnyvale, CA - [Senior Staff AI Accelerator Performance Architect](https://feeny.ai/job/senior-staff-ai-accelerator-performance-architect-cerebras-systems-sunnyvale-ezw8whfqsvhb) — Sunnyvale, CA - [Director, Data Center Counsel](https://feeny.ai/job/director-data-center-counsel-cerebras-systems-sunnyvale-n0r242dny52c) — Sunnyvale, CA