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AI Sustainable Packaging Material Classifier

Chloe Schneider

Full-time · Job · Amsterdam

About the role

Our mission is to make it possible for any brand to know, at a glance, whether their packaging can actually be recycled in the markets where it ships. Computer vision and scikit-learn are what we build our material classification pipeline on, trained against a growing library of packaging samples submitted by brand partners. In this role you'll extend classification coverage to new material types and flag cases where local recycling rules disagree with what the model predicts, working closely with our sustainability research team to keep the model honest about regional differences that actually matter to a brand's compliance reporting.

Responsibilities

  • Extend material classification coverage to new packaging types
  • Flag cases where regional recycling rules diverge from model predictions
  • Maintain the packaging sample library used for training
  • Partner with sustainability research on regional compliance nuances

Requirements

  • 3+ years applying computer vision or classification models
  • Experience with scikit-learn or similar classification frameworks
  • Interest in sustainability or materials science a plus

Benefits

  • Fully remote with flexible hours
  • Health, dental, and vision coverage
  • Meaningful work supporting brand sustainability commitments

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Categories

AI & Machine Learning Engineers

Skills

python computer vision scikit-learn numpy

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Job Type

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Level

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Language

English

Salary Range

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AI Expertise

AI & Machine Learning Engineers

Skills

python computer vision scikit-learn numpy

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