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Cerebras Systems Logo Cerebras Systems · IT - Software Development

Engineering Manager, Kernel Reliability

United States; Canada, Sunnyvale · Job Posted February 17, 2026
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Job Description

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.

Job Responsibility

  • 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 and 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.

Requirements

  • 6+ years in software engineering
  • 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, embedded, etc.)
  • Expertise in 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.)
  • Strong background in monitoring and reliability engineering (incident response, post-mortem analysis, etc.)
  • Demonstrated ability to recruit and retain high-performing teams, mentor engineers, and partner cross-functionally to deliver customer-facing products.

What we offer

  • 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
  • Simple, non-corporate work culture that respects individual beliefs.
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