Introduction
We are seeking a Geospatial AI Engineer who specializes in combining geospatial data with AI technologies to solve complex spatial challenges. If you are passionate about applying machine learning to mapping, geolocation, and earth observation, this role provides the opportunity to make a global impact.
As a Geospatial AI Engineer at our organization, you will design AI pipelines that extract insights from satellite imagery, LiDAR, GPS, and other spatial datasets. You’ll collaborate with data scientists, urban planners, and environmental researchers to deliver innovative geospatial solutions.
We offer competitive compensation, comprehensive benefits, and opportunities to advance cutting-edge geospatial AI systems.
Objectives of this role
- Build and optimize AI systems for geospatial data analysis and mapping.
- Collaborate with stakeholders to design solutions for real-world geospatial problems.
- Apply computer vision and deep learning to remote sensing datasets.
- Ensure system scalability, accuracy, and integration with GIS platforms.
Your tasks
- Develop models for object detection, segmentation, and classification of spatial data.
- Integrate AI pipelines with GIS tools and spatial databases.
- Optimize data pipelines for large-scale geospatial datasets.
- Collaborate with domain experts on applications in agriculture, climate, and defense.
- Validate model outputs with field data and real-world benchmarks.
- Research emerging trends in geospatial AI and incorporate them into solutions.
Required skills and qualifications
- Bachelor’s degree in Computer Science, Geoinformatics, or related field.
- 3+ years of experience in geospatial AI or remote sensing.
- Proficiency in Python and geospatial libraries (GDAL, GeoPandas, Rasterio).
- Experience with ML frameworks (TensorFlow, PyTorch) for vision tasks.
- Strong understanding of spatial databases and GIS platforms.
Preferred skills and qualifications
- Advanced degree in Geospatial AI, Remote Sensing, or Environmental Science.
- Experience with satellite imagery, LiDAR, and aerial drone datasets.
- Familiarity with cloud platforms for geospatial data (AWS, GEE).
- Contributions to open-source geospatial or computer vision projects.
- Knowledge of defense, agriculture, or climate modeling applications.
