What this interview will probe
Owns quality and performance for Cerebras' inference offerings by designing automated eval suites, mining customer workload data to build representative test datasets, and forecasting how those workloads will run on wafer-scale hardware. Builds agent-in-the-loop pipelines and dashboards that consolidate quality and performance metrics across model releases. A technical interview would probe eval design for LLMs (coding, agentic, multimodal), statistical reasoning about benchmark variance, and how you architect a self-running evaluation pipeline.
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