Senior Computer Vision & Spatial Geometry Engineer
hace 2 meses
New York
Job Description Senior Computer Vision & Spatial Geometry Engineer Location: New Yori, NY / Remote Duration: Full Time Role Overview We are building an automated system that converts scanned architectural floor plans (PDFs)—including NYC as-built condominium filings—into structured, coordinate-based spatial data suitable for 3D modeling and GIS workflows. This role focuses on reconstructing accurate geometry from raster scans, not extracting existing vectors and not training end-to-end black-box models. The core challenge is turning noisy, skewed, real-world blueprint scans into watertight room polygons with real-world coordinates. We are looking for a senior engineer who is strong in classical computer vision, computational geometry, and raster-to-vector reconstruction, and who enjoys solving hard, practical problems with deterministic and explainable systems. Key Responsibilities Geometry & Vision Pipeline • Design and implement a raster-to-geometry pipeline for scanned architectural PDFs, • Build robust preprocessing tools for:, • deskewing, • binarization, • noise reduction, • normalization of low-quality scans, • Isolate architectural linework (walls, boundaries) from:, • text, • dimensions, • symbols, • stamps and annotations, • Handle door gaps and broken boundaries to ensure enclosed, “watertight” regions, • Extract enclosed regions (rooms, corridors) using connected components and topology analysis, • Convert raster regions into clean polygon geometry, • contour extraction, • polygon simplification, • vertex snapping, • consistent winding and validity checks Spatial Accuracy & Scaling • Develop deterministic methods to convert pixel geometry into real-world X/Y coordinates, • Calibrate scale using:, • architectural dimension annotations, • scale notes when available, • Validate geometry numerically:, • closed polygons, • area consistency, • tolerance-based error detection Text & Semantic Integration • Integrate OCR outputs to:, • associate room labels with polygons, • parse dimension strings (feet/inches, metric), • extract height or ceiling notes, • Map semantic text to spatial geometry using proximity and containment logic Output & Integration • Produce structured JSON outputs aligned with downstream 3D/GIS systems, • Ensure outputs are explainable, debuggable, and consistent across floors and documents, • Build internal visualization/debugging tools (overlays, masks, polygon previews) What This Role Is Not • Not prompt engineering, • Not LLM application development, • Not training large end-to-end neural networks Required Technical Skills • 5+ years of experience in computer vision, image processing, or computational geometry, • Strong command of classical CV techniques, including:, • thresholding and morphology (dilate/erode/open/close), • edge and line detection (e.g., Hough transforms), • connected components and region analysis, • contour tracing and polygon simplification (e.g., Douglas–Peucker), • Solid understanding of planar geometry and numerical robustness, • Experience converting raster data into vector or polygon representations, • Strong Python skills (NumPy, OpenCV, scikit-image, etc.), • Comfortable debugging visually and iterating on messy real-world data Strongly Preferred • Experience with architectural drawings, floor plans, CAD, BIM, GIS, or maps, • Familiarity with OCR systems and bounding-box–based text extraction, • Experience parsing architectural dimensions (feet/inches or metric), • Experience validating polygon geometry (self-intersection, closure, area), • Prior work on document image analysis or technical drawings Nice to Have • Experience using pretrained segmentation models to supplement classical CV, • Exposure to GIS or BIM formats (GeoJSON, IFC, IMDF), • Knowledge of NYC as-built or Department of Buildings / Finance document conventions, • Experience building internal QA or visualization tools, • Familiarity with downstream 3D geometry pipelines