Engineering Manager, Kernel Reliability

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. Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. 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. The Role We're looking for a deeply technical, hands-on engineering leader for our on-field Kernel Reliability team. You will lead a high performing team to tackle a critical challenge: improving the reliability of our advanced compute clusters and the underlying inference, training, and internal production services. In this role, you'll set the technical vision while staying close to the code and designing solutions that will scale to our exponentially growing system production and software service offerings. If you have proven expertise in software or hardware reliability, diagnostic tool building, or failure analysis and debugging, we want to hear from you. Responsibilities Provide hands-on technical leadership, owning the technical vision and roadmap for the kernel-centric reliability of our internal and customer-facing systems Assist System and Cluster Operations teams on reducing system and service downtime after failure by providing tooling and manual intervention for failure analysis and diagnostic Work with the Debug Team to enhance debug tools with the goal of speeding up failure analysis Collaborate with SW teams to improve the software stack, including Kernels, to improve on-field debugging and failure analysis Work with the ASIC an HW architecture teams to codesign the next generation architectures with reliability and ease of debug in mind Lead, mentor, and grow a high-caliber team of engineers, fostering a culture of technical excellence and rapid execution. Skills & Qualifications 6+ years in software engineering, with 3+ years leading teams in SW/HW reliability, debug, diagnostic, failure analysis or related fields Expertise in parallel and distributed programming (message passing, multicore, GPU, embeded, etc.), debug and diagnostic tool development or expert usage (debuggers, core dump handling, code sanitizers, etc.), experience debugging distributed and parallel applications (deadlocks, livelocks, race conditions, etc.), deep understanding of computer architectures (instruction pipelining, multithreading, networking, etc.) Operations & Monitoring: Strong background in monitoring and reliability engineering (incident response, post-mortem analysis, etc.) Leadership & Collaboration: Demonstrated ability to recruit and retain high-performing teams, mentor engineers, and partner cross-functionally to deliver customer-facing products. Why Join Cerebras 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 of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cu