Applied AI/ML Scientist

<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><h4>About The Role</h4> <p><span data-contrast="auto">As an Applied AI Scientist in the FieldML team, you will be responsible for developing and customizing large language models and more broadly large-scale deep learning models to solve specific customer problems. You won't just advise; you will build. You will bridge the gap between state-of-the-art research and real-world applications by helping customers harness the power of the Cerebras Wafer-Scale Engine (WSE) for their AI initiatives. </span><span data-ccp-props="{}"> </span></p> <p><span data-contrast="auto">We are looking for experienced AI Scientists who are passionate about the "applied" side of machine learning - those who enjoy not just reading papers, but implementing, training, and scaling models to solve complex business and scientific problems. You will work on a diverse range of projects, from training bespoke models from scratch to fine-tuning and optimizing the latest Large Language Models (LLMs) for specific industry verticals, to designing and building components for custom agentic systems.</span><span data-ccp-props="{}"> </span></p> <p><span data-contrast="auto">The ideal candidate has experience in large model training and/or post-training, a deep understanding of training dynamics and model convergence, and expertise in data curation, combined with strong communication skills. </span><span data-ccp-props="{}"> </span></p> <h4><span data-ccp-props="{}">Key Responsibilities </span></h4> <ul> <li><strong><span data-contrast="auto">Customer Use Case Discovery Project Scoping</span></strong><span data-ccp-props="{}"> </span> <ul> <li><span data-contrast="auto">Collaborate with customer stakeholders to identify the best approaches to their business problem with AI.</span><span data-ccp-props="{}"> </span></li> <li><span data-contrast="auto">Contribute to the technical scoping of engagements, including feasibility analysis, data quality/availability/readiness assessments, and the selection of optimal model architectures.</span><span data-ccp-props="{}"> </span></li> <li><span data-contrast="auto">Define project milestones, success metrics, and rigorous evaluation benchmarks to ensure the solution delivers measurable value to the customer’s business.</span><span data-ccp-props="{}"> </span></li> </ul> </li> <li><strong><span data-contrast="auto">Custom SOTA Models and AI Systems Development</span></strong><span data-ccp-props="{}"> </span> <ul> <li><span data-contrast="auto">Architect and execute end-to-end training recipes for custom mode ... (truncated, view full listing at source)