Kernel Engineer - New Grad

Job Title

Kernel Engineer — New Graduate

Role Summary

Develop high-performance ML and linear algebra kernels for the Cerebras Wafer-Scale Engine, a custom massively parallel processor. Work on the intersection of hardware and software to maximize compute utilization and system performance.

Join a kernel team that collaborates with compiler, performance, and hardware engineers to implement, optimize, and validate low-level routines used for ML and HPC workloads.

Experience Level

Entry-level (New graduate).

Responsibilities

Design, implement, and validate high-performance kernel routines and supporting tests for the Cerebras architecture.

• Implement ML and linear algebra kernels targeting the Wafer-Scale Engine.
• Develop and debug low-level code using the Cerebras Software Language and other low-level programming techniques.
• Map computational workloads to the architecture with parallel programming algorithms.
• Use profiling, performance data, and mathematical analysis to evaluate and tune kernels.
• Investigate correctness, performance, and hardware utilization issues.
• Create unit tests and system-level validation methodologies for kernel libraries.
• Collaborate in code reviews and cross-team technical discussions.
• Study emerging ML workloads and contribute to kernel library evolution.
• Build understanding of the architecture, instruction set, memory system, and communication model.

Requirements

Core technical and collaborative skills required for the role.

Must-have

• Strong programming fundamentals in C++ and familiarity with Python.
• Understanding of computer architecture concepts (processors, memory hierarchies, instruction execution, data movement).
• Knowledge of data structures, algorithms, and software development fundamentals.
• Experience debugging software through coursework, internships, research, 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.

Nice-to-have

• Projects, internships, or research involving kernel development, compilers, computer architecture, HPC, or systems programming.
• Familiarity with parallel algorithms, multithreaded programming, or distributed memory systems.
• Exposure to accelerators (GPUs, FPGAs) or experience with CUDA, OpenCL, or assembly-level programming.
• Familiarity with ML frameworks (PyTorch, TensorFlow) and numerical computing or linear algebra kernels.
• Experience using profiling, benchmarking, or performance analysis tools; familiarity with library or API development practices.

Education Requirements

Bachelor's, Master's, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related technical field.

About the Company

Company: Cerebras

Headquarters: Sunnyvale, CA, USA

Developer of wafer-scale AI accelerators, Cerebras designs the Wafer Scale Engine (WSE)—one of the world’s largest AI chips—to deliver high-speed training and inference solutions for model labs, enterprises, and AI-native startups.