Kernel Engineer

Cerebras Systems

Sunnyvale, CA, US
On-site
C++ and python programming
Hardware architecture concepts
Low-level assembly and csl routines
Cerebras Systems is seeking a Kernel Engineer to develop high-performance software solutions that optimize deep learning operations for their innovative wafer-scale AI chip. The role requires expertise in low-level programming and a solid understanding of hardware architecture, aimed at enhancing machine learning and HPC workloads

Job Summary

  • Develop high-performance software for cutting-edge AI and HPC workloads, focusing on implementing, optimizing, and scaling deep learning operations to leverage a custom, massively parallel processor architecture.
  • Design, performance tune, and validate foundational ML and HPC kernels, building a library of parallel and distributed algorithms to maximize compute utilization and accelerate AI innovation.
  • Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next-generation systems, and study emerging trends in Machine Learning applications to evolve Kernel library architecture.

Matching Summary

Match Score: 85

Cerebras Systems is seeking a Kernel Engineer to develop high-performance software solutions that optimize deep learning operations for their innovative wafer-scale AI chip. The role requires expertise in low-level programming and a solid understanding of hardware architecture, aimed at enhancing machine learning and HPC workloads.

Skills & Requirements

Must-have

  • C++ and Python programming
  • Hardware architecture concepts
  • Low-level assembly and CSL routines
  • Parallel programming algorithms
  • Machine learning operations

Nice-to-have

  • Machine learning neural networks
  • HPC kernels optimization
  • Programming accelerators (GPUs, FPGAs)
  • Emerging ML trends

Key Requirements

  • Bachelor’s, Master’s, PhD or foreign equivalents
  • Experience in kernel development and/or testing
  • Familiarity with parallel algorithms
  • Familiarity with distributed memory systems
  • Familiarity with ML frameworks (TensorFlow, PyTorch)

Work Rights

Not specified

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