Senior GeoAI Engineer
Economic and Social Commission for Western Asia · Beirut
Job description
About the role
The United Nations Economic and Social Commission for Western Asia (ESCWA) is seeking a Senior GeoAI Engineer to design, build and operationalize geospatial AI pipelines and services that turn Earth observation data into policy‑relevant indicators for its Arab Member States. The consultant will work within the Decision Support and Data Science Division, strengthening ESCWA’s in‑house geospatial analytics capacity.
Key responsibilities
- Design a scalable, cloud‑based geospatial data architecture for ingestion, storage, processing and serving of raster and vector data (e.g., Sentinel‑1/2, Landsat, VIIRS, commercial imagery, OpenStreetMap).
- Develop, fine‑tune and validate machine‑learning and deep‑learning models for priority use cases, including the use of geospatial foundation models such as Prithvi, SatMAE or SAM.
- Build interactive dashboards and map‑based decision‑support tools that feed sub‑national indicator datasets into ESCWA platforms (ADP, ISPAR, Polaris/Naseej).
- Apply ESCWA’s AI governance principles, produce model cards, and ensure data provenance, privacy and bias assessment.
- Contribute code notebooks and technical examples to the “GeoInsights for Policymaking” practitioner manual and deliver at least two trainings for Member State officials or ESCWA staff.
Required profile
- Master’s degree in geoinformatics, remote sensing, computer science, data science or related field (PhD desirable); or equivalent experience.
- Minimum seven years of progressive experience in geospatial data science or GIS engineering, with at least four years developing and deploying ML/DL models on Earth observation data.
- Proven experience building production‑grade geospatial pipelines on cloud platforms (Google Earth Engine, AWS, Azure, Planetary Computer).
- Fluency in English; knowledge of Arabic is a plus.
Required skills
- Python programming.
- Geospatial libraries: GDAL, rasterio, xarray, GeoPandas, PostGIS.
- Deep‑learning frameworks: PyTorch or TensorFlow.
- Cloud platforms: Google Earth Engine, AWS, Azure, Microsoft Planetary Computer.
- Satellite‑image segmentation, object detection and time‑series analysis.
- Experience with geospatial foundation models (e.g., Prithvi, SatMAE, SAM).
- Knowledge of OGC standards, STAC, COG, GeoParquet, Zarr.
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Published 11 hours ago
Expires 1 month from now
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Economic and Social Commission for Western Asia
Beirut
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