Kernel Engineer

About the Role

As a Kernel Engineer on our team, you will develop high‑performance software solutions that bridge hardware and software, focusing on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture. You will contribute to a world‑class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels, building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state‑of‑the‑art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation.

Responsibilities

• Develop design specifications for new machine learning and linear algebra kernels and map them to the Cerebras WSE System using parallel programming algorithms.
• Develop and debug a kernel library of highly optimized low‑level assembly and C‑like domain specific language routines to implement algorithms targeting Cerebras hardware.
• Use mathematical models and analysis to measure software performance and inform design decisions.
• Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.
• Study emerging trends in machine learning applications and help evolve the kernel library architecture to address computational challenges of state‑of‑the‑art neural networks.
• Interact with chip and system architects to optimize instruction sets, microarchitecture, and I/O of next‑generation systems.

Skills & Qualifications

• Bachelor’s, Master’s, PhD, or foreign equivalent in Computer Science, Computer Engineering, Mathematics, or a related field.
• Proven experience leading technical teams, including mentoring engineers, setting technical direction, and driving execution.
• Strong understanding of hardware architecture concepts and willingness to explore new system architectures.
• Proficiency in C++ and Python with experience in low‑level systems programming.
• Familiarity with library/API development best practices and performance optimization.
• Excellent debugging skills across complex, layered software stacks.

Preferred Skills & Qualifications

• Experience leading teams in kernel development, performance optimization, or low‑level systems programming.
• Strong background in parallel algorithms and distributed memory systems.
• Hands‑on experience with accelerators such as GPUs, FPGAs, or other custom hardware.
• Familiarity with machine learning workloads and frameworks like TensorFlow and PyTorch.
• Understanding of HPC kernels and strategies for optimizing them on modern architectures.

Equal Employment Opportunity

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies.