--- title: 'Cluster Operations Software Engineer at Cerebras Systems' canonical: 'https://feeny.ai/job/cluster-operations-software-engineer-cerebras-systems-sunnyvale-2q1jfv80ge6x' type: 'job' last_seen: '2026-09-08' --- # Cluster Operations Software Engineer at Cerebras Systems - **Company:** [Cerebras Systems](https://feeny.ai/companies/cerebras-systems) - **Location:** Sunnyvale, CA - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-08-13 - **Last confirmed live:** 2026-09-08 - **Apply:** https://jobs.ashbyhq.com/cerebras/f25b9677-32fa-41ed-84d1-0ed704a98533 ## 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. ## THE ROLE We are seeking a highly skilled and experienced AI Cluster Operations Engineer to manage and operate our cutting-edge machine learning compute clusters. These clusters would provide the candidate with an opportunity to work with the world's largest computer chip, the Wafer-Scale Engine (WSE), and the systems that harness its unparalleled power. You will play a critical role in ensuring the health, performance, and availability of our infrastructure, maximizing compute capacity, and supporting our growing AI initiatives. This role requires a deep understanding of Linux-based systems, containerization technologies, and experience with monitoring and troubleshooting complex distributed systems. The ideal candidate is a proactive problem-solver with expertise in large-scale compute infrastructure, dependable and an advocate for customer success. ## RESPONSIBILITIES - Deploy, configure, and debug container-based services using Docker. - Build and own software solutions that power cluster operations, including monitoring platforms, workflow automation systems, operational dashboards, and reliability tooling. - Collaborate with cross-functional teams to translate operational requirements into scalable O&M products and platform capabilities. - Develop APIs, automation services, and integrations that improve operational visibility, incident response, and fleet management across global AI infrastructure. - Manage and operate multiple advanced AI compute infrastructure clusters. - Monitor and oversee cluster health, proactively identifying and resolving potential issues. - Maximize compute capacity through optimization and efficient resource allocation. - Provide 24/7 monitoring and support, leveraging automated tools and performing hands-on troubleshooting as needed. - Handle engineering escalations and collaborate with other teams to resolve complex technical challenges. - Stay up-to-date with the latest advancements in AI compute infrastructure and related technologies. ## SKILLS AND REQUIREMENTS - 6-8 years of relevant experience in managing and operating complex compute infrastructure, preferably in the context of machine learning or high-performance computing. - Proficient in Python and Go, with experience building operational platforms, workflow automation systems, and reliability tooling for large-scale infrastructure environments. - Experience and Expertise in distributed systems is a must. - Deep understanding of Linux-based compute systems and command-line tools. - Extensive knowledge of Docker containers and container orchestration platforms like k8s. - Proven ability to troubleshoot and resolve complex technical issues in a timely and efficient manner. - Experience with monitoring and alerting systems. - Should have a proven track record to own and drive challenges to completion. - Excellent communication and collaboration skills. - Ability to work effectively in a fast-paced environment. - Willingness to participate in a 24/7 on-call rotation. ## PREFERRED SKILLS AND REQUIREMENTS - Operating and Managing large scale AI clusters. - Knowledge of technologies like Ethernet, RoCE, TCP/IP, etc. is desired. - Knowledge of cloud computing platforms (e.g., AWS, GCP, Azure). ## LOCATION - SF Bay Area. - Toronto, Canada. - Bangalore, India. ## 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: 1. Build a breakthrough AI platform beyond the constraints of the GPU. 2. Publish and open source their cutting-edge AI research. 3. Work on one of the fastest AI supercomputers in the world. 4. Enjoy job stability with startup vitality. 5. 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 - [Network Security Engineer](https://feeny.ai/job/network-security-engineer-cerebras-systems-sunnyvale-s1q0rza0gbsf) — Sunnyvale, CA - [Distributed Software Engineer](https://feeny.ai/job/distributed-software-engineer-cerebras-systems-sunnyvale-2y0byqqxk57d) — Sunnyvale, CA - [AI Inference Core - Infrastructure SW Engineer](https://feeny.ai/job/ai-inference-core-infrastructure-sw-engineer-cerebras-systems-sunnyvale-nbqee273jncn) — Sunnyvale, CA - [AI Inference Core - Senior SW Engineer for Platform & DevOps](https://feeny.ai/job/ai-inference-core-senior-sw-engineer-for-platform-devops-cerebras-systems-06p3hxeg5qb7) — Sunnyvale, CA - [AI Inference Core - SDET Technical Lead, Release Integration Testing](https://feeny.ai/job/ai-inference-core-sdet-technical-lead-release-integration-testing-cerebras-fvqxmj75wav1) — Sunnyvale, CA - [ML Systems Integration Engineer](https://feeny.ai/job/ml-systems-integration-engineer-cerebras-systems-sunnyvale-edvsd91tqp93) — Sunnyvale, CA - [Lead Systems Signal Integrity/Power Integrity Engineer](https://feeny.ai/job/lead-systems-signal-integrity-power-integrity-engineer-cerebras-systems-zqq3c0wfj2v1) — Sunnyvale, CA - [Power Engineering Architect](https://feeny.ai/job/power-engineering-architect-cerebras-systems-sunnyvale-xtzeptb5vdc0) — Sunnyvale, CA - [PCB Layout Engineering Lead](https://feeny.ai/job/pcb-layout-engineering-lead-cerebras-systems-united-states-em00ewnccr6z) — United States - [Network Security Engineer (Remote)](https://feeny.ai/job/network-security-engineer-remote-cerebras-systems-united-states-yfrjb08d4wh9) — United States