Staff Kernel Optimization Engineer

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Cerebras

SiteLinkedInTodas as Vagas

501 - 1000 funcionários

🔧 Hardware

🤖 Inteligência Artificial

☁️ SaaS

Hardware • Artificial Intelligence • SaaS

A Cerebras é uma empresa que fabrica chips de IA em escala de wafer (o Wafer-Scale Engine) e sistemas projetados para inferência e treinamento de IA ultra-rápidos. Eles oferecem o sistema CS-3 e a Cerebras Inference Cloud com compatibilidade direta com a API OpenAI, permitindo implantação local, em nuvem e na borda, e fazem parcerias com empresas como AMD, CrowdStrike, Flex e grandes corporações. Sua mensagem de produto destaca chips extremamente grandes (58x maiores que GPUs), velocidade e throughput massivos (até 15x inferência mais rápida, milhares de tokens por segundo) e casos de uso em serviços de modelos, ajuste fino e pré-treinamento. Os clientes incluem OpenAI, Meta, GSK, Mayo Clinic, AWS e outros; as aplicações abrangem infraestrutura de IA, agentes em tempo real, genômica, descoberta de medicamentos, cibersegurança e busca empresarial. A Cerebras foca em hardware de IA de alto desempenho e ofertas de software/plataforma integradas para treinamento e inferência.

Descrição

• 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.

🎯 Requisitos

• 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).

🏖️ Benefícios

• 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.