Senior GeoAI / ML Engineer

Location: London (Hybrid - 1 day per week in our Central London office) Visa Sponsorship: Available for candidates already based in the UK with a valid work visa eligible for transfer (e.g. Skilled Worker, Graduate Visa, Youth Mobility, High Potential Individual, Global Talent) About Tractable Tractable is an applied AI company building computer vision solutions that assess property damage using aerial imagery. Across home and commercial properties, our models process high-resolution imagery to detect damage, estimate costs, and accelerate claims and underwriting for major insurers worldwide. We’re expanding our GeoAI team to scale our computer vision models, geospatial data pipelines, and infrastructure. We’re looking for a Senior GeoAI / ML Engineer to lead the design and deployment of spatial machine learning models, combining remote sensing, deep learning, and geospatial intelligence. The Role As a Senior GeoAI / ML Engineer, you will own the end-to-end development of machine learning models for aerial imagery processing. You will work closely with computer vision researchers, geospatial data engineers, and product teams to turn spatial data into production-ready AI models. What You’ll Do Model Development & Architecture: Design, train, and deploy deep learning models (CNNs, Transformers, Segmentation, Object Detection) optimized for high-resolution aerial and satellite imagery. Geospatial Data Engineering: Build efficient ML data pipelines for processing multi-source spatial data (orthophotos, LiDAR, vector data, satellite imagery) using GDAL, GeoPandas, Rasterio, and STAC. Spatial ML Integration: Combine CV models with spatial metadata (building footprints, land cover, elevation models) to improve damage detection accuracy. MLOps & Scaling: Deploy models into production environments (AWS, Kubernetes, PyTorch, TensorRT), optimizing for latency, throughput, and inference cost. Technical Leadership: Mentor junior engineers, contribute to research directions, and establish best practices for spatial ML modeling and evaluation. What We’re Looking For 5+ years of experience in Machine Learning / Computer Vision, with at least 2+ years focused on GeoAI, Remote Sensing, or Spatial ML. Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow). Hands-on experience with computer vision tasks on aerial/satellite imagery (semantic segmentation, object detection, change detection). Proficiency with geospatial libraries (GDAL, Rasterio, GeoPandas, Shapely, PyProj, QGIS/ArcGIS). Experience with spatial data formats (GeoTIFF, COG, GeoJSON, STAC, Parquet/GeoParquet). Experience building and deploying ML models in cloud environments (AWS / GCP, Docker, Kubernetes). Strong understanding of spatial coordinate reference systems (CRS), projections, and tiling schemes (XYZ, WMTS). Degree in Computer Science, Geospatial Data Science, Remote Sensing, AI/ML, or a related quantitative field. Nice to Have Experience with 3D spatial data (LiDAR, point clouds, Mesh). Familiarity with foundation models for Remote Sensing (e.g., Prithvi, SatMAE, Clay). Contributions to open-source GeoAI or geospatial tools. Why Join Us? Impact: Build AI that directly impacts millions of property owners during natural disasters and climate events. Growth: High-autonomy role in a fast-growing scale-up with strong engineering culture. Culture: Collaborative, engineering-driven environment with regular tech talks and hackathons. Perks: Competitive salary + equity, flexible working, private health insurance, learning budget, and modern Central London office.