Senior Systems Software Engineer, Semiconductor Systems Inspection

Job Title

Senior Systems Software Engineer, Semiconductor Systems Inspection

Role Summary

Develop production-ready AI systems for semiconductor defect inspection, focusing on computer vision, multimodal AI, anomaly detection, model compression, and deployment optimization. Work within a small cross-functional team to convert research approaches into inference pipelines and products that operate within fabrication constraints.

Experience Level

Senior — typically 3+ years of relevant experience in deep learning, machine learning, computer vision, or applied AI.

Responsibilities

Design, prototype, and deliver AI inspection systems and pipelines for semiconductor manufacturing and review workflows.

• Define and prototype system architectures for optical, e-beam, wafer/mask inspection, metrology, and defect review.
• Advance multimodal representation learning, model adaptation, domain transfer, and workflows for data-scarce defect understanding.
• Integrate and improve computer vision pipelines for detection, classification, localization, segmentation, nuisance filtering, ADC, and ADR.
• Design inspection flows for air-gapped fab environments covering data triage, inference, review assistance, root-cause analysis, and secure deployment.
• Leverage metrology and process signals (CD, LER, LWR, overlay, wafer/defect maps, SPC, yield) to improve models and decision support.
• Address noisy, limited, and shifting fab data via calibration, domain-shift mitigation, synthetic defect generation, noise simulation, and augmentation.
• Convert research prototypes into customer-ready products with evaluation, failure analysis, monitoring, optimization, and production deployment paths.
• Collaborate with research, software, process, metrology, inspection, review, and hardware teams to set roadmap priorities.

Requirements

Must-have technical skills and experience required to perform the role.

• 3+ years of proven experience in deep learning, machine learning, computer vision, or applied AI.
• Strong programming skills in Python and practical 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 skills, clear communication, and demonstrated cross-functional collaboration ability.

Nice-to-have:

• 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/production environments.
• Background in anomaly detection or anomaly generation for domains with unusual labels and shifting visual distributions.
• Familiarity with NVIDIA deployment tools (TensorRT, CUDA, cuDNN, Triton, DeepStream, TAO Toolkit, RAPIDS) or building end-to-end production pipelines.

Education Requirements

MS or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.