Principal Systems Software Engineer, Semiconductor Systems Inspection at NVIDIA USA

Compensation · Listed in posting

$272,000 – $431,250/yr

Location: Santa Clara, California
Type: Full-time
Level: staff+
Posted: Sep 16, 2026

Description

NVIDIA is hiring a Principal Systems Software Engineer for Semiconductor Inspection in Santa Clara to architect and deliver production-ready AI systems for optical and e-beam inspection, wafer and mask inspection, metrology, defect review, equipment signals, and process data. The role covers foundation models, computer vision, time-series and multimodal AI, anomaly detection, model adaptation, evaluation, agentic workflows, inference optimization, and deployment in air-gapped fab environments. Candidates need an MS or PhD in a relevant technical field or equivalent experience, 12+ years of software or algorithm engineering, 8+ years in semiconductor manufacturing, and strong Python, PyTorch or TensorFlow, and GPU skills. The base salary is 272,000 USD to 431,250 USD, with equity and benefits.

Required Skills

Computer vision
Time-series modeling
Multimodal AI
Anomaly detection
Model adaptation
Production inference
Python
PyTorch
TensorFlow
GPU literacy

Additional Information

Minimum Education: Master's or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field, or equivalent experience
Required Previous Experiences: 12+ years of professional software or algorithm engineering with technical ownership and architectural direction
8+ years in semiconductor manufacturing, including inspection, metrology, defect review, process control, yield engineering, or fab-data systems
Hands-on delivery of software shipped in semiconductor equipment, operated in a fab, or adopted by a manufacturing customer
4+ years of hands-on deep learning, machine learning, computer vision, or applied AI, including work within the last 24 months
Preferred Qualifications: Experience adapting large pretrained vision, multimodal, or world foundation models to specialized industrial domains
Background in anomaly detection and generation, time-series modeling, FDC, virtual metrology, or advanced-packaging inspection
Experience designing evaluation frameworks for sparse proprietary data and shifting production distributions
Expertise in synthetic data, self-supervised or few-shot learning, domain adaptation, model compression, and inference optimization using NVIDIA technologies
Experience building SDKs, platform capabilities, or agentic workflows adopted by external engineering teams
Translation Company Name: NVIDIA USA