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About The Role Were looking for a deeply technical, hands-on software engineer to join our on-field Kernel Reliability team. You''''ll help 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 work close to the code and design solutions that will scale with our rapidly growing system production and software service offerings. If you have strong fundamentals in systems, debugging, and failure analysisand enjoy building tools and solving hard reliability problemswe want to hear from you. New college graduates are welcome. Responsibilities Contribute to the technical roadmap and execution for kernel-centric reliability of our internal and customer-facing systems. Partner with System and Cluster Operations teams to reduce system and service downtime after failure through tooling, analysis, and hands-on debugging support. Work with the Debug Team to enhance debug tools with the goal of speeding up failure analysis. Collaborate with software teams to improve the software stackincluding kernelsto improve on-field debugging and failure analysis. Work with ASIC and hardware architecture teams to co-design next-generation architectures with reliability and ease of debug in mind. Participate in incident response, root-cause analysis, and post-mortems; drive follow-ups that measurably improve reliability over time. Qualifications We recognize great engineers come from different backgrounds. If you''''re excited about the role, we encourage you to apply even if you don''''t meet every qualification. Required (or demonstrated through projects/internships/coursework): Strong programming skills in C/C++ and Python. Solid foundations in operating systems, computer architecture, and systems programming fundamentals. Ability to debug complex issues using logs, traces, and standard debugging workflows; interest in root-cause analysis. Nice to have Exposure to parallel and distributed programming (message passing, multicore, GPU, embedded, etc.). Experience building or using debug/diagnostic tools (debuggers, core dump handling, tracing, sanitizers, profilers, etc.). Familiarity with debugging distributed and parallel applications (deadlocks, livelocks, race conditions, etc.). Knowledge of computer architecture concepts (instruction pipelining, multithreading, networking, memory systems, etc.). Operations & Monitoring: familiarity with monitoring, incident response, and post-mortem culture. Why Join Cerebras Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Read our blog: Five Reasons to Join Cerebras in 2026. Apply today and become part of the forefront of groundbreaking advancements in AI! We are committed to creating an equal and diverse environment and are proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. 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. This website or its third-party tools processes personal data. For more details, review our CCPA disclosure notice. #J-18808-Ljbffr