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Kernel Optimization Engineer

United Arab Emirates, Dubai · Job Posted February 17, 2026
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Job Description

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.

Job Responsibility

  • Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms
  • Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system
  • Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system
  • Using mathematical models and analysis to measure the software performance and inform design decisions
  • Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries
  • Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks
  • Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems

Requirements

  • Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields
  • Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture
  • Skilled in C++ and Python programming languages
  • Good knowledge of library and/or API development best practices
  • Strong debugging skills and knowledge of debugging complex software stack

Nice to have

  • Experience in kernel development and/or testing
  • Familiarity with parallel algorithms and distributed memory systems
  • Experience in programming accelerators such as GPUs and FPGAs
  • Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch
  • Familiarity with HPC kernels and their optimization

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
  • Our simple, non-corporate work culture that respects individual beliefs

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