Senior Systems Software Engineer, Semiconductor Systems Inspection

Details

NVIDIA is expanding its semiconductor inspection roadmap by developing AI products — models, adaptation workflows, and inference pipelines — for semiconductor customers and partners. The role focuses on turning research into production-ready systems that operate within tight deployment budgets in inspection environments, improving model quality, robustness, and production readiness for industrial inspection scenarios.

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 WFM capabilities for semiconductor inspection, including multimodal representation learning, model adaptation, domain transfer, and data-scarce defect understanding.
• Integrate and enhance computer vision and multimodal inspection workflows for defect detection, classification, localization, segmentation, nuisance filtering, ADC, and ADR in partnership with customers and partners.
• Design agentic inspection flows for air-gapped fab environments, covering 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.
• 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.

Ways to stand out / Preferred

• 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 & Additional Information

• Base salary range: 152,000 USD - 241,500 USD (final base salary determined by location, experience, and pay of employees in similar positions).
• Eligible for equity and benefits.
• Applications accepted at least until June 20, 2026.
• NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer committed to diversity and inclusion.