Staff Kernel Optimzation Engineer
Cerebras Systems7 months ago
Responsibilities
- Design specifications for machine learning and linear algebra kernels and map them to the Cerebras WSE System.
- Develop, debug, and optimize kernel libraries using low-level assembly and the C-like CSL language.
- Implement parallel and distributed algorithms for high-performance AI and HPC workloads.
- Use mathematical models and performance analysis to guide software and hardware design decisions.
- Develop and integrate unit and system testing methodologies for kernel functionality and performance.
- Study emerging machine learning workloads and evolve the kernel library for state-of-the-art neural networks.
- Collaborate with chip and system architects on instruction sets, microarchitecture, and I/O for future systems.
Requirements
- Bachelor’s, master’s, PhD, or foreign equivalent in computer science, computer engineering, mathematics, or a related field.
- Understanding of hardware architecture concepts and willingness to learn new hardware architectures.
- Proficiency in C++ and Python.
- Knowledge of library and API development best practices.
- Strong debugging skills and experience debugging complex software stacks.
- Preferred experience in kernel development or testing, parallel algorithms, distributed memory systems, GPU or FPGA programming, TensorFlow, PyTorch, and HPC kernel optimization.
Benefits
- Opportunity to build an AI platform beyond GPU constraints and work on a high-performance AI supercomputer.
- Opportunities to publish and open-source cutting-edge AI research.
- Job stability with startup vitality and a non-corporate work culture.
- Equal and diverse work environment with continuous learning, growth, and support.
Categories
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.