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

As a Performance Engineer, you will optimize CPU and memory subsystems for high-performance ML workloads on x86 machines, develop algorithms for data movement, and engage with the AI community to enhance our AI platform.

Lead the Inference ML team in developing tools and APIs for large-scale ML applications, enhancing performance and usability, while collaborating across engineering teams.

Design and develop high-performance distributed software for scalable AI training systems, focusing on data pipelines and system efficiency.

The Deployment Engineer will build and operate AI inference clusters, ensure scalable deployments, optimize allocation, and maintain infrastructure. Responsibilities include software updates, telemetry development, and collaborative improvements with teams.

Design and implement low-level components in a compiler toolchain, focusing on LLVM for optimizing code generation for a large AI chip architecture.

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

Develop and automate configuration for distributed clusters, create monitoring tools, manage cloud operations, and ensure system reliability for Cerebras AI supercomputers.

Lead a team to improve the reliability of advanced compute clusters and manage failure analysis and debugging processes.

The Cybersecurity GRC Engineer will enhance compliance processes and build compliant tech solutions, integrating AI for efficiency and risk management.