AI Engineer, Model Quality and Performance

<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.&nbsp;</span><span data-ccp-props="{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335559685&quot;:0,&quot;335559737&quot;:240,&quot;335559738&quot;:240,&quot;335559739&quot;:240,&quot;335559740&quot;:279}">&nbsp;</span></p> <p>Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups.&nbsp;<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.&nbsp;</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><h3><strong>About The Role</strong></h3> <p>You'll own model quality and performance for Cerebras' inference offerings. You will define what "good" looks like across the models we serve, building AI-driven systems to&nbsp; measure it at scale, and translating those signals into artifacts our customers and product team actually use.</p> <p>You'll use AI agents to spin up custom eval suites per customer use case, mine trajectories for representative test data,&nbsp; automate the repetitive parts of release qual, and help build performance datasets and benchmarking workflows for customer use cases. We want someone whose first instinct is "how do I get an AI agent to do this on a loop."</p> <p>You'll sit between engineering, product, and customer-facing teams.&nbsp;</p> <p><strong>What You'll Do</strong></p> <ul> <li><strong>Design eval suites with AI agents in the loop.</strong> For every model release, curate a thoughtful mix of advanced, basic, long-context, and customer-use-case-specific evals. Use Claude to generate, validate, and prune candidate test cases at speed.</li> <li><strong>Build custom evals for target customers </strong>by orchestrating AI agents to mine trajectories from their workloads and synthesize representative eval sets.</li> <li><strong>Automate eval execution end-to-end </strong>with AI-driven pipelines on top of standard tooling (Docker, Git, CI). The goal is a system that runs itself between releases, not a script you re-run by hand.</li> <li><strong>Build automations </strong>to forecast and benchmark model performance on Cerebras for our top customers, including modeling how fast customer-specific workloads will run in production.</li> <li><strong>Build product-quality tooling&nbsp;</strong>that synthesizes quality + performance data into a single, easy-to-use view.&nbsp;</li> </ul> <h3>Skills &amp; Qualifications</h3> <ul> <li><strong>Experience building AI agents.</strong> You ship real systems with Claude (or equivalent) as a force multiplier. You've built things that would have been infeasible solo without AI agents in the loop.</li> <li><strong>Strong math/stats background.</strong>.</li> <li><strong>Comfort with Docker, Git, and the standard automation stack</strong></li> <li><strong>A taste for tooling design. </strong>You've shipped something that a non-engineer used without complaining. Bonus if AI helped you ship it.</li> </ul> <h3>Assets</h3> <ul> <li>Performance-tuning experience on custom silicon, GPUs, or FPGAs.&nbsp;</li> <li>Experience designing evals for agentic / coding / long-context / multimodal use cases.</li> <li>Familiarity with open-source eval frameworks (EvalScope, lm-eval-harness, etc.).</li> <li>Experience building AI agents.</li> </ul><div class="content-conclusion"><h4><strong>Why Join Cerebras</strong></h4> <p>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&nbsp; point in our business. Members of our team tell us there are five main reasons they joined Cerebras:</p> <ol> <li>Build a breakthrough AI platform beyond the constraints of the GPU.</li> <li>Publish and open source their cutting-edge AI research.</li> <li>Work on one of the fastest AI supercomputers in the world.</li> <li>Enjoy job stability with startup vitality.</li> <li>Our simple, non-corporate work culture that respects individual beliefs.</li> </ol> <p>Read our blog:&nbsp;<a href="https://www.cerebras.net/blog/5-reasons-to-join-cerebras" target="_blank" data-auth="NotApplicable" data-linkindex="0">Five Reasons to Join Cerebras in 2026.</a></p> <h4>Apply today and become part of the forefront of groundbreaking advancements in AI!</h4> <hr> <p><em>Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer.&nbsp;</em><em>We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. </em><em>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.</em></p> <hr> <p><em>This website or its third-party tools process personal data. For more details, click <a href="https://www.cerebras.net/privacy/" target="_blank">here</a> to review our CCPA disclosure notice.</em></p></div>