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.
We're 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 analysis—and enjoy building tools and solving hard reliability problems—we 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 stack—including kernels—to 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.
Skills & 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.
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 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!Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. 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.
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Top Skills
What We Do
Cerebras Systems is a team of pioneering computer architects, computer scientists, deep learning researchers, functional business experts and engineers of all types. We have come together to build a new class of computer to accelerate artificial intelligence work by three orders of magnitude beyond the current state of the art.
The CS-2 is the fastest AI computer in existence. It contains a collection of industry firsts, including the Cerebras Wafer Scale Engine (WSE-2). The WSE-2 is the largest chip ever built. It contains 2.6 trillion transistors and covers more than 46,225 square millimeters of silicon. The largest graphics processor on the market has 54 billion transistors and covers 815 square millimeters. In artificial intelligence work, large chips process information more quickly producing answers in less time. As a result, neural networks that in the past took months to train, can now train in minutes on the Cerebras CS-2 powered by the WSE-2.
Join us: https://cerebras.net/careers/
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