Director, Software Engineering - Semiconductor Inspection

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Director of Software Engineering to lead a team building AI and ML technologies for semiconductor manufacturing and automation, focusing on inspection systems, agentic solutions, and integrating multi-modal visual and time-series sensor data into production workflows.

What you'd actually do

  1. Define the vision and architecture for AI-powered semiconductor inspection systems spanning optical, e-beam, wafer and mask inspection, metrology, and defect review — translating research into scalable, production-grade platforms.
  2. Own the strategy for agentic inspection solutions in air-gapped fab environments, covering data triage, model inference, review assistance, root-cause analysis, human-in-the-loop approval, and secure deployment.
  3. Drive integration and evolution of inspection workflows across defect detection, classification, localization, segmentation, nuisance filtering, ADC, and ADR pipelines.
  4. Set the standard for taking research into customer-ready products, with clear evaluation, failure analysis, monitoring, and production deployment paths.
  5. Leading the development of “AI copilots” for semiconductor inspection using NVIDIA’s NIMs and Blueprints.

Skills

Required

  • MS or PhD in VLSI Engineering, Computer Engineering, Electrical Engineering, or a related field (or equivalent experience).
  • 15+ overall years of validated experience in semiconductor manufacturing involving the building and development of tools and processes.
  • 5+ years of leading and managing control of planning, staffing, budgeting, and expense prioritization, as well as recommending and implementing changes to methods
  • Experience collaborating with multiple departments to address common automation challenges.
  • Knowledge of vision and signal-based measurement methods and metrology data workflows.
  • Track record in developing algorithms aimed at predictive analytics and machine learning with demonstrated improvement outcomes.
  • A consistent track record of keeping ahead of the latest trends in manufacturing and automation.
  • Strong communication skills with phenomenal attention to detail.

What the JD emphasized

  • AI-powered semiconductor inspection systems
  • agentic inspection solutions
  • AI applications in production fabrication

Other signals

  • AI-powered semiconductor inspection systems
  • agentic inspection solutions
  • AI applications in production fabrication