Cerebras powers the world's fastest AI inference on the biggest wafer chip. Cerebras CS-4 delivers up to 30x faster inference than GPUs.
About the role
As a Kernel Engineer at Cerebras, you will develop high-performance software at the intersection of hardware and software for cutting-edge artificial intelligence and high-performance computing workloads.
What they're looking for
- Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field
- Strong programming fundamentals in C++ and familiarity with Python
- Understanding of foundational computer architecture concepts such as processors, memory hierarchies, instruction execution, or data movement
- Knowledge of data structures, algorithms, and software development fundamentals
- Experience debugging software through coursework, internships, research, co-op placements, or technical projects
- Strong analytical and problem-solving skills
More about this role
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
As a Kernel Engineer at Cerebras, you will develop high-performance software at the intersection of hardware and software for cutting-edge artificial intelligence and high-performance computing workloads.
You will help implement, optimize, and validate machine learning and linear algebra operations for the Cerebras Wafer-Scale Engine, our custom massively parallel processor architecture. Working alongside experienced kernel, compiler, performance, and hardware engineers, you will learn how...
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