ML Software Tool Development Engineer

<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>Responsibilities:</strong></p> <ul> <li>Lead the design and implementation of system-level debugging, validation, and observability platforms.</li> <li>Develop automated systems for collecting and analyzing numerical, and execution anomalies.</li> <li>Create visualization and analysis tools to enable efficient root-cause investigation.</li> <li>Build frameworks for failure classification, regression detection, and anomaly monitoring.</li> <li>Extend compilers, runtimes, and programming interfaces to support advanced profiling and instrumentation.</li> <li>Improve system bring-up, low-level debug, and validation workflows.</li> <li>Partner cross-functionally with compiler, hardware, firmware, runtime, and infrastructure teams.</li> <li>Establish best practices for debuggability, reliability, and operational excellence.</li> <li>Lead high-impact initiatives.</li> <li>Support incident response and drive long-term corrective actions.</li> </ul> <p><strong> </strong></p> <p><strong>Qualifications: </strong></p> <ul> <li>Strong proficiency in C++ and Python, with a track record of building reliable, high-performance systems and tooling.</li> <li>Demonstrated experience debugging complex hardware/software systems and driving issues to root cause.</li> <li>Experience analyzing system-level data structures, execution graphs, or dependency networks for diagnostics and validation.</li> <li>Proven ability to design and build intuitive visualization and analysis tools for complex technical data.</li> </ul> <ul> <li>Experience with compiler internals, custom hardware interfaces, or low-level protocol design.</li> </ul> <ul> <li>Strong written and verbal communication skills, with the ability to explain technical concepts to diverse stakeholders.</li> <li>Ability to work independently and lead complex technical projects end-to-end.</li> </ul> <p> </p> <p><strong>Preferred Skills Qualifications</strong></p> <ul> <li>Familiarity with machine learning training and inference pipelines, especially distributed training and large-model scaling.</li> <li>Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.</li> </ul> <p> </p><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 point in our business. Members o ... (truncated, view full listing at source)