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AI Automated Optical Sorting Engineer

Alexander Lindqvist

Full-time · Job · Chicago

About the role

Recycling facilities process 40 tons of mixed waste per hour on conveyor belts moving at 3 meters per second. Each item — a plastic bottle, an aluminum can, a cardboard box, a contaminated container — needs to be classified and sorted in under 200ms before it passes the ejection point. Miss it, and valuable recyclables end up in landfill. Misclassify it, and contaminants degrade the output bale quality. Our optical sorting system uses line-scan cameras and near-infrared sensors to classify items at conveyor speed. The challenge is extreme: variable lighting, occluded items, deformable objects, and a conveyor that never stops. You'll improve classification accuracy on the hardest categories — black plastics that absorb NIR, wet cardboard that looks like other materials, and multi-material packaging that belongs in multiple categories simultaneously. You'll work 2 days per week at our Chicago integration lab where we have test conveyors and sensor rigs. The remaining 3 days are remote. The vision team is six engineers; you'll be the senior ML engineer who decides which model improvements are worth the latency trade-off.

Responsibilities

  • Improve classification accuracy on challenging waste material categories
  • Optimize models for sub-200ms inference at conveyor speed
  • Design multi-sensor fusion combining RGB and near-infrared data
  • Build evaluation datasets from real conveyor captures across facilities
  • Balance accuracy improvements against latency constraints
  • Collaborate with hardware engineers on sensor configuration and placement

Requirements

  • 6+ years in computer vision with real-time inference experience
  • Experience with industrial or embedded vision systems
  • Strong PyTorch skills and understanding of model optimization
  • Familiarity with multi-spectral or hyperspectral imaging
  • Comfort with lab environments and physical sensor hardware

Benefits

  • Hybrid — 2 days Chicago lab, 3 days remote
  • Competitive salary plus equity
  • Health, dental, and vision from day one
  • $3,500 annual conference budget
  • Direct environmental impact — every improvement reduces landfill waste

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Categories

AI & Machine Learning Engineers Automation & AI Workflows

Skills

python pytorch computer vision docker aws

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