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AI Thermal Imaging Analysis Engineer

Alexander Lindqvist

Full-time · Job · Chicago

About the role

Thermal cameras see what RGB cameras miss. A PCB with a failing solder joint looks normal in visible light but glows in infrared. A pharmaceutical tablet with an air pocket is indistinguishable visually but shows as a cold spot thermally. Our inspection platform combines both modalities, and thermal analysis is the part that still requires human expert review 40% of the time. You'll build the computer vision models that automate thermal defect classification. The datasets exist — four years of labeled thermal scans across 12 manufacturing clients. The challenge is handling sensor variability: different camera models, calibration drift over time, and ambient temperature changes that shift the baseline. Your models need to be robust to these real-world conditions, not just benchmark-accurate. The role is hybrid: 2 days per week in our Chicago lab for hardware testing sessions, the rest remote. You'll join a vision team of five engineers, taking ownership of the thermal pipeline while collaborating with the RGB team on fusion models.

Responsibilities

  • Build defect detection and classification models for thermal imaging data
  • Design data augmentation strategies for sensor variability and calibration drift
  • Implement multi-modal fusion between thermal and RGB inspection streams
  • Build evaluation pipelines that track accuracy across different sensor configurations
  • Run inference optimization to support real-time inspection line throughput
  • Collaborate with manufacturing clients to collect and label new edge case data

Requirements

  • 3+ years in computer vision engineering with production deployment experience
  • Hands-on experience with thermal or infrared imaging is a strong plus
  • Strong PyTorch skills and familiarity with multi-modal architectures
  • Understanding of manufacturing quality inspection workflows
  • Experience building training pipelines for class-imbalanced industrial datasets

Benefits

  • Hybrid: 2 days lab, 3 days remote
  • Health, dental, and vision insurance
  • 401(k) with 4% match
  • $3,000 annual conference and training budget
  • Patent bonus program for novel inspection techniques

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch computer vision docker aws

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Skills

python pytorch computer vision docker aws numpy

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