Kernel Engineer - New Grad
Cerebras Systems2 months ago
Responsibilities
- Design and implement machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine.
- Develop, debug, and performance-tune high-performance kernel routines using low-level programming techniques and the Cerebras Software Language.
- Apply parallel algorithms to map workloads efficiently onto the Cerebras architecture.
- Use mathematical analysis, profiling tools, and performance data to evaluate kernel behavior and guide design decisions.
- Investigate correctness, performance, and hardware-utilization issues.
- Develop unit tests and system-level validation methods for 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 kernel library.
- Participate in code reviews, technical discussions, and software development processes.
- Develop 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.
- Strong programming fundamentals in C++ and familiarity with Python.
- Understanding of computer architecture concepts including 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.
- Interest in low-level software, parallel computing, performance optimization, or hardware/software co-design.
- Preferred qualifications include kernel development, compiler, computer architecture, HPC, or systems-programming research, internships, or projects.
- Preferred qualifications include familiarity with parallel algorithms, multithreaded programming, distributed memory systems, GPUs, FPGAs, assembly language, CUDA, OpenCL, domain-specific languages, PyTorch, TensorFlow, numerical computing, linear algebra, profiling, benchmarking, performance analysis, and library or API development.
Benefits
- Opportunity to build software for a breakthrough AI platform beyond GPU constraints.
- Opportunities to publish and open-source cutting-edge AI research.
- Opportunity to work on a high-performance AI supercomputer.
- Job stability with startup vitality and a non-corporate work culture.
- Equal opportunity employer committed to an inclusive and diverse work environment.
About Cerebras Systems
Cerebras Systems designs and sells AI compute systems built around its wafer-scale WSE-3 processor, delivered as the CS-3 appliance and via the Cerebras Cloud. It targets enterprises, model labs, and government users needing fast training and inference, and offers on‑prem and cloud deployments. Privately held and headquartered in Sunnyvale, California, the company announced a multi-year partnership with OpenAI to deploy large-scale inference capacity.