The board
Cerebras · University Departments- Where
- Sunnyvale, CA
- Posted
- Jul 23
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.
What you'd do
- 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.
What they want
- 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.
What you get
- 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.
About Cerebras · University Departments
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.