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Principal Systems Software Engineer, Semiconductor Systems Inspection

NVIDIA· Engineer, Sys SW
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Santa Clara, CA$272k - $431.3kfull-timePosted 1mo ago

About the role

Hands-on architect role to define, build, evaluate, and demonstrate AI-enabled semiconductor inspection systems. Develop architectures and workflows spanning optical/e-beam inspection, metrology, defect analysis, and production-inference within air-gapped fab environments. Collaborate across research, software, process, metrology, inspection, and hardware teams to enable partner-integrated, production-ready solutions.

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 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 production latency, memory, throughput, reliability, and security budgets for partner deployment.
  • 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.

Qualifications

  • MS or PhD in Computer Science, Electrical Engineering, Computer Engineering, or related field, or equivalent experience.
  • 12+ years of professional software or algorithm engineering with architectural direction.
  • 8+ years in semiconductor manufacturing including inspection, metrology, defect review, process control, yield engineering, or fab-data systems.
  • Hands-on delivery of software shipped in semiconductor equipment, operated in a fab, or adopted by a manufacturing customer.
  • 4+ years of hands-on deep learning, machine learning, computer vision, or applied AI, including recent work.
  • Strong Python skills and production experience with PyTorch or TensorFlow.
  • Track record of taking ambiguous technical problems through architecture, implementation, evaluation, and validated results.
  • Working GPU literacy for inference performance and bottleneck analysis.
  • Direct engagement with fabs, manufacturing teams, or equipment vendors on technical requirements.
  • Strong analytical, communication, and cross-functional leadership skills.

Skills

Required:PythonPyTorchDeep Learning / Computer VisionSystem ArchitectureDomain knowledge in semiconductor manufacturing
Nice to have:TensorFlow

Benefits

  • equity
  • benefits package (complete details at NVIDIA benefits page)
Last updated Sep 18, 2026. Interested? Apply on the company site.

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