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.
About The Role
As a Kernel Engineer on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture.
You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.
Responsibilities
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.
Skills And Qualifications
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.
Preferred Skills And Qualifications
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.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
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.
Find out more about what it's like to work at Cerebras here!
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
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Skills Required
- Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Mathematics, or related field
- Understanding of hardware architecture concepts
- Skilled in C++ and Python
- Good knowledge of library and API development best practices
- Strong debugging skills and ability to debug complex software stacks
- Comfortable learning the details of a new hardware architecture
- Experience in kernel development and/or testing
- Familiarity with parallel algorithms and distributed memory systems
- Experience programming accelerators such as GPUs and FPGAs
- Familiarity with machine learning frameworks (TensorFlow, PyTorch)
- Familiarity with HPC kernels and their optimization
What We Do
Cerebras Systems develops wafer-scale semiconductor hardware, AI supercomputers, and software/cloud services for training and inference. Its CS-2 and CS-3 systems help organizations build on-premise AI supercomputers, while pay-as-you-go cloud offerings provide developers and enterprises access to its computing platform. The company focuses on making AI training and inference faster and easier for diverse research and production workloads at scale worldwide.
