Geospatial Data Annotator — Shrimp Aquaculture in Cardiff

About Longline

Longline Environment Ltd is a UK-registered environmental consultancy specialising in aquaculture risk, remote sensing, and spatial planning. Our AquaScape platform provides high-resolution pond and cage registry data to insurers, certification bodies, and aquaculture operators across Asia, Africa, and the Mediterranean. We are building machine learning datasets to automate the extraction of pond morphology and farm infrastructure from drone and satellite imagery.

Role overview

We are recruiting an experienced annotator to build a high-resolution training dataset for machine learning models designed to detect and characterise shrimp pond infrastructure from aerial and satellite imagery. You will label pond boundaries, inlet/outlet structures, embankments, aerator positions, and associated farm features across a range of imagery resolutions and geographic contexts. Accuracy, consistency, and domain knowledge of shrimp pond systems are essential.

Key responsibilities

• Annotate high-resolution drone imagery (Mavic 4 Pro and equivalent) and satellite imagery (Planet, Maxar) of shrimp pond farms for ML training purposes.
• Label pond polygons, embankment edges, inlet/outlet canals, aerators, paddlewheels, and ancillary farm infrastructure with precision.
• Apply consistent annotation schemas across varied farm types: intensive, semi-intensive, traditional/extensive, and silvofishery ponds.
• Validate and quality-check annotations produced by other team members.
• Maintain annotation logs and flag ambiguous or low-quality imagery for review.
• Work within QGIS or equivalent GIS environments to manage spatial annotation layers.
• Coordinate with the GIS & ML Lead on label taxonomy, class definitions, and edge cases.
• Deliver annotated datasets in agreed formats (GeoJSON, COCO, YOLO) on schedule.

Required qualification and experience

• Minimum 2 years of hands-on experience working in or directly with shrimp pond operations (farm manager, field technician, extension officer, or equivalent).
• Practical familiarity with shrimp pond farm layouts: pond geometries, embankment construction, water management infrastructure, and aeration systems.
• Ability to distinguish between species-specific pond types (Litopenaeus vannamei, Penaeus monodon) and production system intensity from aerial imagery.
• Understanding of pond lifecycle stages and how farm appearance changes seasonally and across production cycles.

• Proficient in QGIS for polygon digitising, layer management, and spatial data export.
• Comfortable working with high-resolution raster imagery and georeferenced files (GeoTIFF, orthomosaics).
• Familiarity with GeoJSON and/or shapefile formats.
• Basic understanding of coordinate reference systems and image scale.

• High attention to detail and ability to maintain annotation consistency across large datasets.
• Proficient in written English for communication with the Longline team.
• Reliable internet connection for file transfer and remote collaboration.
• Ability to meet deadlines and report progress every week.

• Experience with ML annotation tools (Label Studio, CVAT, Roboflow, or similar).
• Familiarity with COCO JSON or YOLO annotation formats.
• Prior experience annotating drone or satellite imagery for remote sensing applications.
• Knowledge of shrimp aquaculture in Southeast Asia (Thailand, Vietnam, Indonesia, Ecuador) or the Middle East.
• Intermediate Python or scripting experience for annotation format conversion.

What we offer

• Competitive freelance day/task rate commensurate with experience.
• Fully remote, flexible working arrangement.
• Involvement in a technically ambitious ML project with real-world application in global aquaculture.
• Opportunity to extend into longer-term geospatial or AquaScape data work within the Longline team.

How to apply

Please send the following to with the subject line Shrimp Annotator Application:

• A brief cover note (max 300 words) describing your shrimp farming background and GIS experience.
• Your CV or professional profile.
• One or two examples of GIS or annotation work (screenshots or files acceptable).
• Your day rate or preferred rate structure and availability to start.

Applications are reviewed on a rolling basis. Early applications are encouraged.