Staff Kernel Optimization Engineer

🕒 July 28

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

👷🏻‍♀️ Engineer

👻 Ghost score 14%

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Cerebras

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🔧 Hardware

🤖 Artificial Intelligence

☁️ SaaS

Hardware • Artificial Intelligence • SaaS

Cerebras is a company that builds wafer-scale AI chips (the Wafer-Scale Engine) and systems purpose-built for ultra-fast AI inference and training. They offer the CS-3 system and Cerebras Inference Cloud with drop-in OpenAI API compatibility, enable on-premise, cloud, and edge deployment, and partner with companies like AMD, CrowdStrike, Flex, and major enterprises. Their product messaging emphasizes extremely large chips (58x larger than GPUs), massive speed and throughput (up to 15x faster inference, thousands of tokens per second), and use cases across model serving, fine-tuning, and pre-training. Customers include OpenAI, Meta, GSK, Mayo Clinic, AWS, and others; applications span AI infrastructure, real-time agents, genomics, drug discovery, cybersecurity, and enterprise search. Cerebras focuses on high-performance AI hardware and integrated software/platform offerings for training and inference.

📋 Description

• Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms. • Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system. • Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system. • Using mathematical models and analysis to measure the software performance and inform design decisions. • Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries. • Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks. • Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.

🎯 Requirements

• Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields. • Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture. • 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. • Experience in kernel development and/or testing (preferred). • Familiarity with parallel algorithms and distributed memory systems (preferred). • Experience in programming accelerators such as GPUs and FPGAs (preferred). • Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch (preferred). • Familiarity with HPC kernels and their optimization (preferred).

🏖️ Benefits

• Build a breakthrough AI platform beyond the constraints of the GPU. • Publish and open source their cutting-edge AI research. • Work on one of the fastest AI supercomputers in the world. • Enjoy job stability with startup vitality. • Our simple, non-corporate work culture that respects individual beliefs.