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Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- Build CV/ML pipelines for engineering drawings, PDFs, aerial imagery, and satellite imagery
- Extract information from vector and raster PDFs, including degraded/scanned drawings
- Develop detection and segmentation models for materials and infrastructure such as asphalt, concrete, pavement, drainage, pipes, signs, guardrails, and lane markings
- Combine information from drawings, specifications, and imagery, identifying discrepancies between sources
- Build ML infrastructure around models, including labeling, datasets, evaluation, regression testing, confidence, and provenance
- Work directly with domain experts to create ground truth and improve the system
- Prioritize reliability and completeness, favoring “not determinable” over low-confidence guesses
- Own identification of materials, surfaces, and construction features for an AI-powered quantity-takeoff platform
- Collaborate with an engineering role focused on geometry and measurement to produce reliable, priceable quantities
Requirements
What you’ll need- 5+ years building and shipping production Computer Vision / ML systems
- Strong Python and PyTorch experience
- Production experience with detection and segmentation on real-world imagery
- Experience with aerial, satellite, drone, or comparable raster imagery
- Strong knowledge of OpenCV and classical CV techniques
- Experience with messy, domain-specific data and human-in-the-loop systems
- Understanding of PDF internals, vector geometry, and/or document AI, or the ability to learn quickly
- Strong written and verbal English
- Experience with geospatial imagery, construction, document AI/OCR, CAD vectorization, or autonomous vehicle perception
- 3D experience with photogrammetry, point clouds, terrain/surface models, or cut & fill
- Experience across both document vision and aerial/geospatial CV
Benefits
Comp & perks- Contract directly with the client
- Remote work
- Full-time schedule