RESPONSIBILITIES
Help design and implement machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine.
Develop and debug high-performance kernel routines using low-level programming techniques and the Cerebras Software Language, a custom C-like language.
Apply parallel programming algorithms to map computational workloads efficiently onto the Cerebras architecture.
Use mathematical analysis, performance data, and profiling tools to evaluate kernel behavior and inform design decisions.
Identify and investigate correctness, performance, and hardware utilization issues.
Develop unit tests and system-level validation methodologies to verify the functionality and performance of kernel libraries.
Collaborate with kernel, compiler, performance, and hardware engineers to improve software and system performance.
Study emerging machine learning workloads and contribute to the evolution of the kernel library.
Participate in code reviews, technical discussions, and software development processes.
Build an understanding of the Cerebras architecture, instruction set, memory system, and communication model.
MINIMUM SKILLS & QUALIFICATIONS
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.
Interest in low-level software, parallel computing, performance optimization, or hardware/software co-design.
Ability to learn unfamiliar systems and collaborate effectively within a technical team.
PREFERRED SKILLS & QUALIFICATIONS
Research, internships, or projects involving kernel development, compilers, computer architecture, HPC, or systems programming.
Familiarity with parallel algorithms, multithreaded programming, or distributed memory systems.
Exposure to programming accelerators such as GPUs, FPGAs, or other specialized processors.
Experience with low-level programming, assembly language, CUDA, OpenCL, or a domain-specific language.
Familiarity with machine learning concepts, neural networks, or frameworks such as PyTorch or TensorFlow.
Exposure to numerical computing, linear algebra, or HPC kernels.
Experience using profiling, benchmarking, or performance analysis tools.
Familiarity with library or API development practices.
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:
1. Build a breakthrough AI platform beyond the constraints of the GPU.
2. Publish and open source their cutting-edge AI research.
3. Work on one of the fastest AI supercomputers in the world.
4. Enjoy job stability with startup vitality.
5. Our simple, non-corporate work culture that respects individual beliefs.
Find out more about what it's like to work at Cerebras here https://www.cerebras.ai/join-us!
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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