Kernel Engineer

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 highly optimized kernel-library routines using low-level assembly instructions and the custom C-like Cerebras Software Language (CSL), targeting the Cerebras hardware system.
• Use mathematical models and performance analysis to inform software design decisions.
• Develop and integrate unit and system testing methodologies to verify the functionality and performance of kernel libraries.
• Study emerging machine learning applications and evolve kernel-library architecture to address computational challenges in state-of-the-art neural networks.
• Collaborate with chip and system architects to optimize instruction sets, microarchitecture, and I/O for next-generation systems.

Requirements

• Bachelor's, master's, PhD, or foreign equivalent in Computer Science, Computer Engineering, Mathematics, or a related field.
• Understanding of hardware architecture concepts and willingness to learn the details of new hardware architectures.
• Proficiency in C++ and Python.
• Knowledge of library and API development best practices.
• Strong debugging skills and ability to debug complex software stacks.

Nice-to-haves

• Experience with kernel development or testing.
• Familiarity with parallel algorithms and distributed-memory systems.
• Experience 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 kernel optimization.