Cerebras
Kernel Engineer - New Grad
Sunnyvale, CA · Hybrid · Entry level · Full-time · Posted Jul 23, 2026
- Experience
- No years specified; debugging experience may come from coursework, internships, research, co-op placements, or technical projects.
- Education
- Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.
About the job
Develop, optimize, and validate machine-learning and linear-algebra kernels for Cerebras’s Wafer-Scale Engine, improving performance and hardware utilization.
What you'll do
- Design, implement, debug, and tune kernels using low-level programming and parallel algorithms.
- Analyze kernel performance and correctness using profiling, mathematical analysis, testing, and validation.
- Collaborate with kernel, compiler, performance, and hardware engineers on software and system improvements.
What they ask 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, and knowledge of data structures, algorithms, and software development fundamentals.
- Experience debugging software through coursework, internships, research, co-op placements, or technical projects.
Nice to have
- Research, internships, or projects involving kernel development, compilers, computer architecture, HPC, or systems programming.
- Familiarity with parallel algorithms, accelerators, low-level programming, machine learning, numerical computing, or performance analysis tools.
Tools
C++, Python, Cerebras Software Language, CUDA, OpenCL, PyTorch, TensorFlow
AI focus
Develop and optimize machine-learning kernels and support emerging machine-learning workloads on Cerebras hardware.
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