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STACK Construction TechnologiesPosted 1 month ago
EXPIRED

Senior Computer Vision Engineer- Canada

$250,000–$280,000 year

RemoteUnited States

Part TimeSenior LevelSmall

Job Summary

Design end-to-end detection and segmentation pipelines for construction document images, improving ingestion for PDFs and unstructured files through parsing, rendering, and multi-page handling. Increase model accuracy, boundary quality, and geometric precision while integrating modern architectures into production workflows with robust post-processing. Define evaluation metrics, investigate failure cases, and optimize latency, reliability, and cost across the inference stack. Own training infrastructure, dataset curation, and continuous-improvement loops to ensure systems perform consistently under real-world constraints.

Required Qualifications

  • Experience building computer vision systems: detection, segmentation, or structured geometry extraction, used high volume in production
  • Experience working with messy, real-world image data or large unstructured visual datasets
  • Strong understanding of detection and segmentation tradeoffs, including model architecture choices, training data design, and post-processing
  • Ability to measure system performance with evaluation, testing, and production metrics
  • Ability to explain failure modes clearly and improve systems through debugging, dataset work, and iteration
  • Experience with multimodal models (vision-language models, document AI systems)
  • Understanding of grounding — linking model outputs to source data or coordinates
  • Backend engineering experience, including APIs, async processing, and scalable GPU services

Desired Qualifications

  • Experience with polygon or mask post-processing, geometric regularization, or CAD-style structured output
  • Experience with layout-aware document processing, PDF vector extraction, or combining raster and vector signals
  • Background in document-heavy CV domains such as construction, real estate, medical imaging, geospatial, or similar workflows
  • Experience optimizing inference cost and latency at scale
  • Familiarity with open-source detection / segmentation ecosystems, training infrastructure, or model serving

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