Job Description
Role Overview
nWe are seeking a high-energy, curious, and versatile Lead Geospatial AI Engineer to head our
nGeoAI R&D; team. In this role, you will be the technical architect behind our most complex
ncomputer vision problems and the operational lead driving multiple projects to success. You
nmust be comfortable pivoting between deep research, hands-on coding, and strategic team
nmanagement in a fast-paced, agile setting.
nKey Responsibilities
nTeam Leadership & Mentorship: Lead a cross-functional team of AI engineers; foster a
nculture of curiosity, continuous learning, and rapid experimentation.
nAgile Project Execution: Oversee the end-to-end lifecycle of multiple R&D; projects, ensuring
ntimely delivery of prototypes and production-ready models.
nAdvanced R&D;: Research and implement state-of-the-art (SOTA) computer vision
narchitectures (e.g., Vision Transformers, Diffusion Models, Segment Anything) for diverse
ngeospatial analytics.
nScalable AI Pipelines: Design robust MLOps workflows to handle massive multi-modal
ndatasets (Satellite, SAR,



LiDAR, Aerial) from ingestion to deployment.
nCross-Functional Collaboration: Partner with product and business leads to translate
nabstract research into actionable industry solutions for sectors like [Climate
nTech/Defense/Urban Planning].
nTechnical Stack Requirements
nCore AI & Computer Vision:
nFrameworks: Mastery of PyTorch (preferred) or TensorFlow.
nCV Libraries: Expert use of OpenCV, TorchVision, SAMGeo, Detectron2, and YOLO variants.
nAdvanced Modeling: Experience with Hugging Face Transformers for Vision and Segment
nAnything (SAM).
n

nGeospatial Engineering Stack:
nProcessing: Expert proficiency with GDAL/OGR, Rasterio, and GeoPandas.
nGeometry: Deep knowledge of Shapely and Pyproj for CRS management.
nAnalysis: Experience with Google Earth Engine, TorchGeo, and QGIS/ArcGIS Pro.
nData & MLOps Infrastructure:
nCloud Platforms: Extensive experience with AWS (SageMa

📌 Lead Geo-Spatial AI Engineer (Bengaluru)
🏢 Qrata
📍 Bengaluru