C

Cerebras

AI accelerator hardware replacing GPUs

Kernel Engineer

Systems Software EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A Bachelor’s, Master’s, PhD, or foreign equivalent degree in Computer Science, Computer Engineering, Mathematics, or a related field is required.
  • Understanding of hardware architecture concepts and the ability to learn the details of a new hardware architecture.
  • Proficiency in C++ and Python programming languages.
  • Knowledge of library and application programming interface development best practices.
  • Strong debugging skills and knowledge of debugging complex software stacks.

Responsibilities

  • Develop design specifications for new machine learning and linear algebra kernels and map them to the Cerebras WSE System using parallel programming algorithms.
  • Develop and debug a kernel library of highly optimized low-level assembly instructions and C-like domain-specific language routines targeting the Cerebras hardware system.
  • Develop and debug high-performance kernel routines in low-level assembly and the custom C-like Cerebras Software Language, implementing algorithms optimized for the Cerebras hardware system.
  • Use mathematical models and analysis to measure software performance and inform design decisions.
  • Develop and integrate unit and system testing methodologies to verify the functionality and performance of kernel libraries.
  • Study emerging trends in machine learning applications and help evolve kernel library architecture to address computational challenges of state-of-the-art neural networks.
  • Interact with chip and system architects to optimize instruction sets, microarchitecture, and input/output of next-generation systems.

Desired Qualifications

  • Experience in kernel development and/or testing.
  • Familiarity with parallel algorithms and distributed memory systems.
  • Experience programming accelerators such as graphics processing units and field-programmable gate arrays.
  • Familiarity with machine learning neural networks and frameworks such as TensorFlow and PyTorch.
  • Familiarity with high-performance computing kernels and their optimization.

About the Company

Cerebras

AI accelerator hardware replacing GPUs

Cerebras Systems creates AI acceleration hardware and software. Its CS-2 system is designed to replace traditional GPU clusters for AI workloads, speeding up training and inference while simplifying the setup by eliminating the need for parallel programming, distributed training, and cluster management. The product works as a single, large processor-based accelerator with accompanying software and cloud services to run AI models efficiently, reducing latency and time to results. Compared with competitors, Cerebras differentiates itself with the largest processor in the industry and an integrated hardware-software stack that aims to streamline AI workflows rather than relying on multi-GPU clusters. The company's goal is to help research labs, healthcare, finance, and other industries achieve faster, more cost-effective AI development and deployment by offering a turnkey high-performance AI compute solution.

Company size
501-1,000
Company stage
IPO
Headquarters
Sunnyvale, CA
Founded
2016

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