Senior Systems Software Engineer, Semiconductor Systems Inspection

Nvidia

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$152,000–$241,500 / yr
Posted
2 days ago

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Competitive pay

How this pay compares to similar roles

Similar $185k
This role $197k
$138k most similar roles pay here $253k

This role pays more than 57% of similar roles. Most pay $148,878–$222,000 — the shaded band above. At the midpoint, this role pays about $197k versus about $185k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 997 open roles on FindRole.

Listed pay typically runs $168,000–$270,250 across 984 roles with salary data.

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At a glance

TL;DR · Senior Systems Software Engineer, Semiconductor Systems Inspection

NVIDIA seeks a Senior Software Engineer to drive its semiconductor inspection roadmap by developing cutting-edge AI products such as models, adaptation workflows, and inference pipelines. This role involves transforming innovative approaches into practical systems that meet strict deployment budgets in fabrication environments, focusing on computer vision, multimodal AI, anomaly detection, model compression, and optimization. The engineer will collaborate with partners to enhance existing workflows for defect detection and classification, design agentic inspection flows, and integrate semiconductor metrology data to improve model quality and decision support. Key responsibilities include addressing challenges like limited data and domain shifts, converting research into deployable products, and partnering across teams to define priorities for next-generation AI inspection systems. The ideal candidate has a strong background in deep learning, computer vision, Python programming, and experience with frameworks like PyTorch or TensorFlow, as well as familiarity with NVIDIA’s deployment tools such as TensorRT and Triton.

What you'll do

  • Define and prototype AI system architectures for semiconductor defect inspection workflows.
  • Advance WFM capabilities for semiconductor inspection, including multimodal representation learning and model adaptation.
  • Integrate and enhance existing computer vision workflows with partners for defect detection and classification.
  • Design agentic inspection flows for air-gapped fab environments, ensuring secure deployment constraints are met.
  • Convert research into customer-ready semiconductor inspection products with clear evaluation and production deployment paths.

What we're looking for

  • MS or PhD in Computer Science, Electrical Engineering, or related field.
  • 3+ years experience in deep learning, machine learning, computer vision, or applied AI.
  • Strong programming skills in Python and proficiency with PyTorch or TensorFlow.
  • Experience developing foundational world models for classification, detection, segmentation, anomaly detection, or multimodal understanding.
  • Familiarity with self-supervised, few-shot, weakly supervised, unsupervised, or domain adaptation approaches.
  • Knowledge of NVIDIA software tools like TensorRT, CUDA, cuDNN, Triton, DeepStream, TAO Toolkit, RAPIDS.
  • Experience building end-to-end AI pipelines for data curation, training, evaluation, export, and inference in production settings.

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