Teams at Cerebras Systems Inc.

Lead performance modeling and architecture analysis for next-generation AI accelerators. Build analytical, simulation-based, and trace-driven models; analyze AI workloads and hardware bottlenecks; evaluate architectural features; validate models against RTL, emulation, and silicon data; and provide recommendations that influence hardware and software roadmaps. Partner with architecture, compiler, kernel, runtime, and systems teams to improve latency, throughput, utilization, and energy efficiency.

Leads end-to-end technical programs for AI compute systems and data center deployments. Owns engineering improvement schedules, hardware change implementation, software integration, validation, risk mitigation, and cost management. Coordinates product, engineering, manufacturing, supply chain, procurement, and software teams while presenting program status and risks to senior leadership. Develops scalable processes and ensures hardware and software deliverables meet performance, budget, and schedule objectives.

Own and scale major areas of Cerebras’s Developer Console, including billing, usage tracking, quotas, request logs, and metrics. Design frontend systems and backend services using Next.js, TypeScript, GraphQL, Postgres, and Redis. Make architectural decisions across APIs, data models, distributed systems, and real-time processing. Lead projects from conception through production, improve reliability and observability, partner with product and design, and mentor engineers.