Senior Systems Software Engineer, Semiconductor Systems Inspection

Details

NVIDIA is expanding its semiconductor inspection roadmap by developing practical AI products, including models, adaptation workflows, and inference pipelines, for inspection environments with limited data, domain shifts, and tight deployment budgets. The role focuses on turning research approaches into production-ready systems for semiconductor manufacturing projects in Santa Clara.

Responsibilities

• Define and prototype AI system architectures for semiconductor defect inspection across optical inspection, e-beam inspection, wafer and mask inspection, metrology, and defect review workflows.
• Advance wafer fab monitoring capabilities through multimodal representation learning, model adaptation, domain transfer, and data-scarce defect understanding.
• Integrate and enhance computer vision and multimodal workflows for defect detection, classification, localization, segmentation, nuisance filtering, automatic defect classification, and automatic defect review.
• Design agentic inspection flows for air-gapped fabrication environments, connecting data triage, model inference, review assistance, root-cause analysis, human approval, and secure deployment constraints.
• Use 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.
• Convert research into customer-ready semiconductor inspection products with clear evaluation, failure analysis, monitoring, optimization, and production deployment paths.
• Partner with research, software, process, metrology, inspection, review, and hardware teams to define roadmap 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.
• At least 3 years of proven experience in deep learning, machine learning, computer vision, or applied AI.
• Strong programming skills in Python 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.
• Familiarity with self-supervised, few-shot, weakly supervised, unsupervised, or 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, training, evaluation, export, and inference in production settings.

Compensation and Benefits

• Base salary range: USD 152,000–241,500 per year.
• Eligible for equity and benefits.
• Applications accepted at least until June 20, 2026.
• NVIDIA is an equal opportunity employer committed to an inclusive work environment.