Data Platform Engineer

Cerebras Systems
Sunnyvale, CA$160k – $250kPosted 1 March 2026

Job Description

<div class="content-intro"><p><span data-contrast="none">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. </span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335559685":0,"335559737":240,"335559738":240,"335559739":240,"335559740":279}"> </span></p> <p>Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. <a href="https://openai.com/index/cerebras-partnership/">OpenAI recently announced a multi-year partnership with Cerebras</a>, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. </p> <p>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.</p></div><p><strong><span data-contrast="auto">About the Role</span></strong><span data-ccp-props="{}"> </span></p> <p><span data-contrast="auto">As a Platform Engineer on the Cerebras Data Analytics team, you will design, build, and maintain a reliable, high-performance cloud data platform that enables the company’s success via data-driven insights. Your work will amplify the impact of data engineers and data scientists to address diverse needs across hardware, software, operations, and business intelligence. The ideal candidate is a proactive, independent problem solver who takes pride in delivering efficient and effective solutions.</span><span data-ccp-props="{}"> </span></p> <p><strong><span data-contrast="auto">Responsibilities</span></strong><span data-ccp-props="{}"> </span></p> <ul> <li data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-contrast="auto">Design, deploy, and maintain core infrastructure in AWS for data storage, processing, and reporting.</span><span data-ccp-props="{}"> </span></li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="2" data-aria-level="1"><span data-contrast="auto">Maintain and scale databases and data lakes that store ever-increasing volumes of data.</span><span data-ccp-props="{}"> </span></li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="3" data-aria-level="1"><span data-contrast="auto">Create tools, automations, and frameworks to improve developer efficiency.</span><span data-ccp-props="{}"> </span></li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="4" data-aria-level="1"><span data-con ... (truncated, view full listing at source)