Compute Server Platform Architect

Benefits

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Not verified checked Jun 7, 2026

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401(k) match

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Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Staff Plus From the posting source checked Jun 20, 2026

Schedule

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Weekend work

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Company

Company stage

Public-company From the posting source checked Jun 20, 2026

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About this role

Compute Server Platform Architect Sunnyvale CA or Toronto Canada Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. About The Role As a Compute / Server Platform Architect on the Cluster Architecture Team, you will own the server-side platform architecture that enables Cerebras CS3-based AI clusters (training and inference) to deliver predictable performance, scalability, and reliability. Our accelerators are network-attached, so the x86 server fleet is a first-class part of the end-to-end system: it runs critical-path runtime functions (for example orchestration, prompt caching, and IO/control services) and must be co-designed with software for token-level latency, throughput, and cost efficiency. You will

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