
Computer Vision Engineer
Posted 1 day ago

Posted 1 day ago
This is a fully remote position, open to applicants in Argentina.
• Develop computer vision and machine learning pipelines for engineering drawings, PDFs, aerial imagery, and satellite imagery.
• Extract data from vector and raster PDFs, including degraded and scanned drawings.
• Create detection and segmentation models for various materials and infrastructure, including asphalt, concrete, pavement, drainage, pipes, signs, guardrails, and lane markings.
• Integrate information from drawings, specifications, and imagery while identifying discrepancies among sources.
• Establish machine learning infrastructure surrounding models, such as labeling, datasets, evaluation, regression testing, confidence, and provenance.
• Collaborate directly with domain experts to establish ground truth and enhance the system.
• Emphasize reliability and completeness, preferring “not determinable” over low-confidence predictions.
• Take ownership of identifying materials, surfaces, and construction features for an AI-driven quantity-takeoff platform.
• Work alongside an engineering role concentrated on geometry and measurement to ensure reliable and cost-effective quantities.
• 5+ years of experience in building and deploying production-level Computer Vision / ML systems.
• Proficient in Python and PyTorch.
• Hands-on experience with detection and segmentation on real-world imagery.
• Familiarity with aerial, satellite, drone, or similar raster imagery.
• In-depth knowledge of OpenCV and classical computer vision techniques.
• Experience handling messy, domain-specific data and implementing human-in-the-loop systems.
• Understanding of PDF internals, vector geometry, and/or document AI, or the capacity to learn rapidly.
• Excellent written and verbal communication skills in English.
• Background in geospatial imagery, construction, document AI/OCR, CAD vectorization, or autonomous vehicle perception.
• Experience in 3D with photogrammetry, point clouds, terrain/surface models, or cut & fill.
• Proficiency in both document vision and aerial/geospatial computer vision.
• Direct contract with the client.
• Opportunity for remote work.
• Full-time schedule.
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