Cerebras Systems
Kernel Engineer - New Grad
Sunnyvale, CA · Junior · Internship
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About the role
- Working alongside experienced kernel, compiler, performance, and hardware engineers, you will learn how algorithms are mapped to specialized hardware and contribute to software that maximizes compute utilization and system performance.
- This is an excellent opportunity for a new graduate who is interested in computer architecture, parallel programming, low-level software, and machine learning systems.
Responsibilities
- Develop and debug high-performance kernel routines using low-level programming techniques and the Cerebras Software Language, a custom C-like language.
- Use mathematical analysis, performance data, and profiling tools to evaluate kernel behavior and inform design decisions.
- 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.
- Build an understanding of the Cerebras architecture, instruction set, memory system, and communication model.
Requirements
- Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.
- Knowledge of data structures, algorithms, and software development fundamentals.
- Experience debugging software through coursework, internships, research, co-op placements, or technical projects.
- Familiarity with parallel algorithms, multithreaded programming, or distributed memory systems.
- Experience with low-level programming, assembly language, CUDA, OpenCL, or a domain-specific language.
- Experience using profiling, benchmarking, or performance analysis tools.
- Familiarity with library or API development practices.
- 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.
- 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.
- Research, internships, or projects involving kernel development, compilers, computer architecture, HPC, or systems programming.
- Exposure to programming accelerators such as GPUs, FPGAs, or other specialized processors.
- Familiarity with machine learning concepts, neural networks, or frameworks such as PyTorch or TensorFlow.
- Exposure to numerical computing, linear algebra, or HPC kernels.
Skills
- Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups.
Benefits
- Help design and implement machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine.
- Study emerging machine learning workloads and contribute to the evolution of the kernel library.
Company info
- 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.
This listing is sourced directly from Cerebras Systems's careers page and normalized into a canonical job model.