Principal Systems Software Engineer, Semiconductor Systems Inspection

Details

NVIDIA is expanding its semiconductor inspection capabilities by developing practical AI products, including models, adaptation workflows, and inference pipelines for real-world inspection environments with limited data, domain shifts, and strict deployment constraints. The team is developing anomaly-generation and inspection workflows for semiconductor manufacturing.

The Principal Software Engineer for Systems Inspection will develop AI products for semiconductor analysis and help make research production-ready for manufacturing projects. The role spans computer vision, multimodal AI, anomaly detection, model compression, and deployment optimization, with a focus on improving model quality, robustness, and operational readiness for industrial inspection scenarios.

Responsibilities

• Define and prototype AI system architectures for semiconductor defect inspection across optical and e-beam inspection, wafer and mask inspection, metrology, and defect-review workflows.
• Advance WFM capabilities for semiconductor inspection, including multimodal representation learning, model adaptation, domain transfer, and data-scarce defect understanding.
• Partner with customers and internal teams to integrate and improve computer vision and multimodal workflows for defect detection, classification, localization, segmentation, nuisance filtering, ADC, and ADR.
• Design agentic inspection flows for air-gapped fab environments that connect data triage, model inference, review assistance, root-cause analysis, human approval, and secure deployment constraints.
• Apply semiconductor metrology, inspection, review, and process context—including CD, LER, LWR, overlay, wafer maps, defect maps, SPC signals, and yield signals—to improve model quality and fab decision support.
• Address noisy, limited, and shifting fab data through tool-to-tool calibration, domain-shift mitigation, synthetic defect generation, noise simulation, and augmentation.
• Turn research into customer-ready semiconductor inspection products with clear approaches to evaluation, failure analysis, monitoring, optimization, and production deployment.
• Work with research, software, process, metrology, inspection, review, and hardware teams to set priorities for next-generation semiconductor AI inspection systems.

Requirements

• MS or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field, or equivalent experience.
• 15+ years of proven experience in systems design, architecture, and software development.
• 4+ years of current experience in deep learning, machine learning, computer vision, or applied AI.
• Strong Python skills and experience with modern deep learning frameworks such as PyTorch or TensorFlow.
• Experience developing or applying foundational world models in computer vision for classification, detection, segmentation, anomaly detection, or multimodal understanding.
• A record of technical leadership in domain-adaptation approaches relevant to inspection problems.
• Strong analytical, communication, and cross-functional collaboration skills.

Preferred Qualifications

• Experience with semiconductor inspection, industrial visual inspection, manufacturing AI, metrology, or defect-review workflows.
• Experience with knowledge distillation, model compression, quantization, pruning, or deployment optimization for edge or production environments.
• Background in anomaly detection or anomaly generation, especially in domains with unusual labels and shifting visual distributions.
• Familiarity with NVIDIA software and deployment tools such as TensorRT, CUDA, cuDNN, Triton, DeepStream, TAO Toolkit, or RAPIDS.
• Experience building end-to-end pipelines spanning data curation and training.

Benefits

• Base salary range of USD 272,000–431,250 per year, determined by location, experience, and the pay of employees in similar positions.
• Eligibility for equity and benefits.
• NVIDIA is an equal opportunity employer committed to an inclusive work environment.
• Applications will be accepted at least until August 28, 2026.