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AI Stereo Vision Calibration Engineer

Hannah Cohen

Full-time · Job · Los_Angeles

About the role

Stereo cameras enable metric 3D reconstruction without structured light or lidar — but the depth quality is only as good as the calibration. A calibration that's 0.3 pixels off on the epipolar geometry produces depth errors that accumulate across a scene and make downstream 3D understanding unreliable. Most production stereo systems get calibrated once at the factory and gradually drift; almost none have automated in-field recalibration. Our 3D vision platform serves robotics companies and autonomous systems integrators. Calibration robustness is our biggest reliability differentiator: systems that maintain accurate depth in changing temperatures, after physical shocks, and across lighting conditions outperform systems with better optics that drift uncalibrated. You'll build the automated stereo calibration and online recalibration system: designing calibration procedures that work with scene-level features when calibration targets aren't present, implementing online recalibration that detects drift and corrects it without human intervention, and building the calibration quality metrics that alert operators when depth accuracy falls below application thresholds. This is senior IC work at the intersection of classical computer vision and learned components.

Responsibilities

  • Design automated stereo calibration pipeline using scene features when calibration targets are unavailable
  • Implement online recalibration detecting epipolar geometry drift and correcting it in real time
  • Build calibration quality metrics alerting operators when depth accuracy degrades
  • Develop temperature and vibration compensation models for extrinsic parameter drift
  • Create calibration validation framework testing accuracy against known 3D ground truth
  • Optimize calibration algorithms to run on embedded systems with limited compute

Requirements

  • 6+ years in computer vision engineering with stereo vision and camera calibration experience
  • Deep understanding of projective geometry, epipolar constraints, and stereo reconstruction
  • Strong Python skills with OpenCV and calibration toolchain experience
  • Experience with online estimation and filter-based state tracking for calibration parameters
  • Track record delivering reliable 3D vision systems in demanding production environments

Benefits

  • Fully remote with flexible schedule
  • Top-of-market compensation for 3D vision expertise
  • Comprehensive health benefits
  • $5,000 annual equipment and conference budget
  • Equity participation

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch computer vision docker aws

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