Principal Systems Software Engineer, Semiconductor Systems Inspection

Responsibilities

• Define and prototype AI system architectures spanning optical and e-beam inspection, wafer and mask inspection, metrology, defect review, equipment signals, and process data.
• Advance world foundation model capabilities for semiconductor manufacturing, including vision, time-series and multimodal representation learning, model adaptation, domain transfer, and data-scarce defect understanding.
• Develop workflows for defect detection, classification, localization, segmentation, nuisance filtering, ADC, ADR, and equipment time-series anomaly detection.
• Establish evaluation methods that measure model quality and robustness under tool-to-tool and fab-to-fab domain shift, diagnose failures, and define production-readiness thresholds.
• Design fab-local evaluation and adaptation workflows that preserve customer data sovereignty and produce comparable evidence across partner deployments.
• Connect inspection and metrology results with equipment signals, process history, wafer genealogy, SPC, and yield outcomes to support manufacturing-wide reasoning and root-cause analysis.
• Design agentic workflows for air-gapped fabs that connect data triage, model inference, review assistance, root-cause analysis, human approval, and secure deployment.
• Optimize and package inference capabilities to meet real production latency, memory, throughput, reliability, and security budgets, allowing partners to deploy without NVIDIA operating their systems.
• Work directly with fabs and equipment manufacturers to move capabilities from prototype to partner-operated production.
• Collaborate across research, software, process, metrology, inspection, and hardware teams to define platform capabilities and the technical roadmap for semiconductor AI.

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