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Cerebras SystemsCerebras SystemsUnited States

Kernel Engineer - New Grad

Develops and optimizes low-level machine learning and linear algebra kernels for Cerebras's Wafer-Scale Engine. The role is suited to a new graduate with strong C++ fundamentals and interest in computer architecture, parallel programming, performance optimization, and hardware/software co-design.

Salary not listed
HybridEntry levelBackend Engineering

About the role

Responsibilities

  • Help design and implement machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine.
  • Develop and debug high-performance kernel routines using low-level programming techniques and the Cerebras Software Language, a custom C-like language.
  • Apply parallel programming algorithms to map computational workloads efficiently onto the Cerebras architecture.
  • Use mathematical analysis, performance data, and profiling tools to evaluate kernel behavior and inform design decisions.
  • Identify and investigate correctness, performance, and hardware utilization issues.
  • Develop unit tests and system-level validation methodologies to verify the functionality and performance of kernel libraries.
  • Collaborate with kernel, compiler, performance, and hardware engineers to improve software and system performance.
  • Study emerging machine learning workloads and contribute to the evolution of the kernel library.
  • Participate in code reviews, technical discussions, and software development processes.
  • Build an understanding of the Cerebras architecture, instruction set, memory system, and communication model.

Requirements

  • Bachelor's, master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.
  • Strong programming fundamentals in C++ and familiarity with Python.
  • Understanding of foundational computer architecture concepts, including processors, memory hierarchies, instruction execution, and data movement.
  • Knowledge of data structures, algorithms, and software development fundamentals.
  • Experience debugging software through coursework, internships, research, co-op placements, or technical projects.
  • Strong analytical and problem-solving skills.
  • Interest in low-level software, parallel computing, performance optimization, or hardware/software co-design.
  • Ability to learn unfamiliar systems and collaborate effectively within a technical team.

Nice-to-haves

  • Research, internships, or projects involving kernel development, compilers, computer architecture, HPC, or systems programming.
  • Familiarity with parallel algorithms, multithreaded programming, or distributed memory systems.
  • Exposure to programming accelerators such as GPUs, FPGAs, or other specialized processors.
  • Experience with low-level programming, assembly language, CUDA, OpenCL, or a domain-specific language.
  • Familiarity with machine learning concepts, neural networks, or frameworks such as PyTorch or TensorFlow.
  • Exposure to numerical computing, linear algebra, or HPC kernels.
  • Experience using profiling, benchmarking, or performance analysis tools.
  • Familiarity with library or API development practices.

Compensation and Benefits

  • Build a breakthrough AI platform beyond the constraints of the GPU.
  • Publish and open source cutting-edge AI research.
  • Work on one of the fastest AI supercomputers in the world.
  • Enjoy job stability with startup vitality.
  • Work in a non-corporate culture that respects individual beliefs.
  • Cerebras Systems is committed to an equal and diverse environment and supports continuous learning, growth, and collaboration.

Skills

C++Pythoncerebras software languageparallel programmingcomputer architectureData StructuresAlgorithmsMachine Learninglinear algebrahpcCUDAopenclPyTorchTensorFlowprofiling

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