Network Systems Architect: Low-Latency AI Fabric

Engg; Sunnyvale (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Cerebras Systems in Sunnyvale, CA, seeks a Network Systems Architect to define scale-up network architecture for Cerebras platforms, including proprietary interconnects, protocols, and switching. You will translate workloads into fabric requirements with a focus on low-latency performance and cross-team collaboration.

You will write specifications, guide models and prototypes, and influence end-to-end system behavior through implementation, bring-up, and qualification across multiple generations.

Responsibilities

• Set the multi-generation architecture and roadmap for Cerebras scale-up networks and their interfaces to scale-out and customer-facing networks.
• Work with application, compiler, runtime, and communication-library teams to understand mapping and communication choices, then derive the required bandwidth, latency, ordering, availability, and serviceability.
• Define fabric topology, protocols, and switch behavior, including routing, buffering, flow control, reliability, and fault containment. Connect data-plane choices to end-to-end system behavior.
• Decide when to use standards-based technology or merchant silicon and when a custom protocol, switch, link, or offload is justified.
• Use performance models, traffic simulation, prototypes, and lab data to test architecture choices and set acceptance criteria.
• Write architecture and interface specifications, lead design reviews, and drive cross-layer decisions through implementation, bring-up, and qualification.

Job description

Cerebras Systems in Sunnyvale, CA, seeks a Network Systems Architect to define scale-up network architecture for Cerebras platforms, including proprietary interconnects, protocols, and switching. You will translate workloads into fabric requirements with a focus on low-latency performance and cross-team collaboration.

You will write specifications, guide models and prototypes, and influence end-to-end system behavior through implementation, bring-up, and qualification across multiple generations.