FPGA Engineer

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation. Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership https://openai.com/index/cerebras-partnership/ with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. ABOUT THE ROLE The Host and Network IO Team develops the full IO path implementation between a distributed system of server nodes, through the cluster, down to the custom RoCE network stack implemented in Cerebras' system, and over the proprietary IOs onto the WSE. As an FPGA developer on the team, you will own the in-chassis IO subsystem consisting of i) several cluster-facing RoCE v2 network interfaces via a custom implementation of the RDMA protocol; ii) a large programmable switching fabric; and iii) Serial IO communication with the Cerebras WSE via a proprietary protocol. You will interface between AI application-level IO teams, cluster architecture teams, and embedded software teams to develop solutions that optimize bandwidth and latency while minimizing congestion, pauses, pause spreading, unfairness, etc. The scope of work spans multiple generations of hardware products from improvements to presently deployed hardware, implementation of upcoming systems, and design/architecting of future next-gen architectures. RESPONSIBILITIES - Lead full chassis-to-wafer IO architecture and design - Improve current RTL, implement next-gen FPGA design, define future IO architectures - Produce production-ready bitstreams for deployment into l

Department: Software; Team: Software