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Design and develop microarchitecture and RTL for wafer-scale AI chips. Lead functional specification, RTL development, synthesis and front-end integration. Collaborate with physical design, verification, DFT, software and systems teams to meet PPA goals. Debug silicon-level functional, timing, and power issues and manage third-party IP and vendor interactions to deliver production silicon.

Lead PCB design from specification through implementation, bring-up, qualification, and production. Own schematics, component selection, and layout. Perform lab bring-up, debugging, and automated benchtop test development. Collaborate with manufacturing, test, supply chain, ASIC, mechanical, signal integrity, power delivery, layout, embedded, and diagnostics teams.

The role involves developing infrastructure for benchmarking AI inference performance, analyzing system behavior, designing telemetry systems, and collaborating with teams to improve feature performance.

The Deployment Engineer will manage AI inference clusters, optimizing deployment, capacity allocation, and ensuring reliability of pipeline operations across datacenters.

The role involves synthesizing, placing, and routing high-speed designs, collaborating with RTL teams, and optimizing designs for power/performance area.

The Senior Performance Analyst will benchmark Cerebras' AI inference performance, analyze competitor pricing, and provide pricing recommendations to enhance the customer value proposition, requiring deep expertise in ML frameworks and architecture.

The Business Operations Lead will partner with senior leaders to manage operations in the Datacenter organization, ensuring alignment and efficient execution of plans and priorities, while improving transparency and decision-making mechanisms.

As a Network Architect, you'll design AI/ML and HPC clusters, address performance bottlenecks, drive multi-team projects, and collaborate with vendors.

Manage AI compute clusters, monitor systems health, optimize resources, and troubleshoot technical issues, ensuring high performance for ML applications.

Develop and maintain the architecture for Cerebras' Inference Cloud Platform, focusing on distributed systems, performance optimization, and technical direction. Responsibilities include coding, design reviews, and mentoring senior engineers.