Data Annotation Intern

We are looking for a Data Annotations intern with hands-on experience in annotating Earth Observation (EO) and Synthetic Aperture Radar (SAR) imagery for advanced computer vision and geospatial AI tasks. You will be a key contributor in building high-quality labeled datasets to be used to train and validate computer-vision models. This is an internship position for a period of 3 months. Subject to project needs, and individual performance, the internship may be considered for conversion to a full-time role. Responsibilities Annotation & Labeling Annotate features including targets and infrastructure in EO (optical, multi-spectral) and SAR imagery, across different acquisition modes and resolutions. Image segmentation or pixel-level masks depending on the schema of annotations required. Flag imagery affected by cloud cover, haze, or sensor noise that may compromise annotation quality. Handle annotations across multiple sensor modalities (EO–EO, SAR–SAR, EO–SAR). Annotate paired EO/SAR scenes across designated Areas of Interest (AOIs), maintaining consistency across dataset batches. Geospatial & Data Handling Work with geo-referenced raster data (GeoTIFF, etc.) and vector data (json, geojson, .gpkg, .shp, etc.) Ensure spatial alignment and consistency between multi-temporal and multi-sensor datasets. Validate annotations against ground truth, reference layers, or auxiliary GIS data. Quality Control Maintain high annotation accuracy and consistency across datasets. Perform peer reviews and quality audits on annotated data. Identify edge cases, ambiguous regions, and sensor-specific artifacts. Collaboration with ML Teams Collaborate with ML engineers and researchers to: Refine labeling guidelines Improve class definitions and taxonomy Provide feedback on model errors and data gaps Assist in creating annotation protocols and documentation. Requirements Required Qualifications Education: Pursuing or recently completed a bachelor's degree. Eagerness to learn about satellite sensors workflows, Satellite Image Processing, and DL/ML dataset curation. Requirements: Exposure to satellite images and geospatial data. Experience with EO, SAR, or geospatial datasets. Usage of GIS Softwares e.g., QGIS, ArcGIS, ERDAS Imagine, etc. Exposure to Roboflow, CVAT, LabelMe and other geospatial annotation platforms. Benefits What You'll Gain Hands-on exposure to real satellite EO/SAR datasets used in production of ML pipelines. Direct mentorship from the AI & CV team on geospatial data workflows.