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AI Product Dimension Measurement Vision Engineer

Alexander Lindqvist

Full-time · Job · Detroit

About the role

Dimensional measurement on a manufacturing line currently requires a human with calipers, a CMM machine with setup time measured in hours, or a structured light scanner that costs $80,000 and works only on specific surface types. For high-volume production of small parts, none of these scale. Vision-based dimensional measurement does — if you can make it accurate to 0.1mm from a single camera frame. We serve 38 precision manufacturing clients who need automated dimensional verification: gaskets, fasteners, stamped metal components, injection-molded parts. The measurement challenge is sub-millimeter accuracy from a camera 60cm above a conveyor belt moving at 2 meters per second. Camera calibration, lens distortion correction, real-world scale mapping, and depth estimation from a single RGB image are the core technical problems. You'll own the dimensional measurement vision system: calibration pipeline, single-image dimension estimation models, accuracy validation against CMM ground truth, and the per-part measurement confidence scoring that flags out-of-tolerance items for rejection. Your models run on edge hardware with 50ms inference budget.

Responsibilities

  • Build camera calibration and lens distortion correction pipeline for production-line cameras
  • Develop single-image dimensional estimation models accurate to 0.1mm on target part categories
  • Implement real-world scale mapping from pixel measurements to physical dimensions
  • Create measurement confidence scoring identifying out-of-tolerance parts for rejection
  • Validate accuracy against CMM ground truth across the part type library
  • Optimize inference pipeline to meet 50ms budget on edge hardware

Requirements

  • 3+ years in computer vision engineering with measurement or metrology applications
  • Strong Python and PyTorch skills with camera calibration and projection geometry experience
  • Familiarity with edge deployment and inference optimization constraints
  • Experience with manufacturing quality or dimensional inspection use cases preferred
  • Ability to validate model accuracy against physical measurement ground truth

Benefits

  • Fully remote with quarterly site visits to manufacturing clients
  • Health and dental insurance
  • $3,000 annual professional development budget
  • 401(k) with match
  • Equity options

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Categories

AI & Machine Learning Engineers Automation & AI Workflows

Skills

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