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AI Visual Inspection Lead

Alexander Lindqvist

Full-time · Job · London

About the role

Semiconductor fabs produce wafers worth $50,000 each. A single defect missed during inspection can cascade through the manufacturing process, ruining entire production lots. Our visual inspection system catches defects that human inspectors miss — at 100x the throughput. As visual inspection lead, you'll manage the full detection pipeline: from raw wafer images to defect classification, severity scoring, and automated disposition recommendations. You'll lead a team of 3 CV engineers, set the technical roadmap, and work directly with fab engineers who understand the defect physics but need help translating that knowledge into detection algorithms. The hardest problem isn't detection accuracy — it's detection speed. Inspection throughput directly limits production capacity. Every millisecond of inference latency costs money. You'll optimize models for sub-10ms inference on edge hardware while maintaining the accuracy standards that fab quality teams demand.

Responsibilities

  • Lead the visual defect detection pipeline from image capture to disposition
  • Manage a team of 3 computer vision engineers
  • Optimize inference latency for sub-10ms detection on edge hardware
  • Set the technical roadmap for inspection accuracy and throughput improvements
  • Collaborate with fab engineers to translate defect physics into detection models

Requirements

  • 6+ years in computer vision with manufacturing or inspection experience
  • Strong PyTorch skills and model optimization expertise
  • Experience leading small engineering teams
  • Understanding of edge deployment and inference optimization
  • Track record shipping CV systems in production environments

Benefits

  • Fully remote — UK and EU time zones
  • Senior compensation with equity
  • $4,000 annual conference budget
  • Leadership role with direct production impact

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Categories

AI & Machine Learning Engineers AI Product & Strategy

Skills

python pytorch computer vision docker kubernetes

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