Engineering Manager, Inference Platform

Cerebras Systems
Sunnyvale CA or Toronto CanadaPosted 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="none">Location: Toronto / Sunnyvale</span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></p> <p><span data-contrast="none">We're looking for a deeply technical, hands-on engineering leader for our Inference Service Platform. You will lead a high performing team to tackle a critical challenge: scaling LLM inference on Cerebras’ advanced compute clusters and delivering a world-class, on-prem solution for enterprise customers. In this role, you’ll set the technical vision while staying close to the code, architecting highly reliable, low latency distributed systems. If you have proven expertise in distributed systems and scaling modern model-serving frameworks, we want to hear from you.</span><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></p> <p><strong><span data-contrast="none">Responsibilities</span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></p> <ul> <li data-leveltext="" data-font="Symbol" data-listid="10" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-contrast="none">Provide hands-on technical leadership, owning the technical vision and roadmap for the Cerebras Inference Platform, from internal scaling to on-prem customer solutions.</span><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="10" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="2" data-aria-level="1"><span data-contrast="none">Lead the end-to-end development of distributed inference systems, including request routing, autoscaling, and resource orchestration on Cerebras' unique hardware.</span><span data-ccp-props="{"134233117":false,"134233118":false,"335559738":0,"335559739":0}"> </span></li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="10" data-list-defn-props="{"335552541":1,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="3" data-aria-level="1"><span data-contrast ... (truncated, view full listing at source)