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Cerebras Systems

AI insights, faster! We're a computer systems company dedicated to accelerating deep learning.

Senior Kernel Optimization Engineer

EngineerEngineerFull TimeRemoteSeniorTeam 201-500Since 2016H1B SponsorCompany SiteLinkedIn

Location

California

Posted

82 days ago

Salary

0

Seniority

Senior

Postgraduate DegreeEnglishAssemblyPythonPyTorchTensorflow

Job Description

Senior Kernel Optimization Engineer

Cerebras Systems

• 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.

Job 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.
  • 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.

Benefits

  • 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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