Staff Kernel Optimzation Engineer

The role

You will develop high-performance software solutions for AI and HPC workloads. You will implement, optimize, and scale deep learning operations to leverage custom massively parallel processor architecture.

What you will do

• Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System.
• Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines.
• Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language.
• Use mathematical models and analysis to measure software performance and inform design decisions.
• Develop and integrate unit and system testing methodologies to verify kernel libraries.
• Study emerging trends in Machine Learning applications to evolve Kernel library architecture.
• Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.

Required qualifications

• Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.
• Understanding of hardware architecture concepts.
• 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.

Nice to have

• 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.

About the company

Cerebras Systems builds the world's largest AI chip. The company works with leading model labs, global enterprises, and cutting-edge AI-native startups.