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Lead a team of engineers to develop high-performance software solutions for AI and HPC workloads while mentoring team members and overseeing technical direction.

Join the SOTA Training Platform team to bring up ML models on Cerebras systems, enhancing performance across the software stack and debugging issues.

Design and architect front-end network fabrics for AI/ML and HPC clusters. Automate deployment of network infrastructure, debug networking issues, and lead technical projects across teams.

The Sr. Technical Staff will validate silicon for wafer-scale engines, conduct high-speed interface testing, and develop automated regression tests. They will collaborate with engineering teams for hardware optimization, diagnosing issues, and ensuring compliance with design specifications.

Lead the design and development of high-performance RTL solutions for the Cerebras Wafer Scale Engine, collaborating with teams and managing ASIC vendors.

Design, implement, optimize, and validate high-performance ML and linear algebra kernels for Cerebras hardware. Develop low-level assembly and CSL routines, measure and tune performance, build testing methodologies, and collaborate with chip and system architects to maximize compute utilization for AI and HPC workloads.

Join the Kernel Reliability team to improve the reliability of compute clusters, assist in debugging, and enhance system tools alongside hardware teams.

Join the Inference Core Model Bringup team to bring up ML models on Cerebras CSX systems, focusing on performance, optimization, and debugging.

Lead a team in developing and scaling distributed inference systems for AI on Cerebras' hardware, ensuring reliability and performance while mentoring engineers.

The R&D Engineer will design and implement performance workloads on Cerebras' wafer-scale hardware, collaborating across teams to advance AI and scientific computing. Responsibilities include optimizing performance models, contributing to the technology roadmap, and publishing research findings.