Senior Geospatial Machine Learning Engineer

📋 Description

• Develop and deploy vegetation intelligence products using ML, deep learning, computer vision
• Explore geospatial datasets, identify model improvements, optimize ML solutions, and troubleshoot
• Maintain and enhance vegetation modeling products for accuracy, reliability, and scalability.
• Lead technical projects end-to-end from planning to delivery and evaluation.
• Develop measurement frameworks and performance metrics for data-driven decisions on model quality
• Monitor production models using observability and debugging tools.

🎯 Requirements

• 5+ years in ML/DS roles with production ML/deep learning experience.
• Proven CV/deep learning experience with satellite/aerial imagery.
• Strong Python and geospatial libraries (rasterio, geopandas, shapely, GDAL).
• Solid understanding of geospatial data structures and processing workflows.
• Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn).
• Experience designing/maintaining data pipelines with Dagster, Airflow, dbt, etc.

🎁 Benefits

• Fully remote working environment.
• Opportunity to work on climate action, wildfire prevention, and grid resilience.
• Meaningful ownership of ML products and end-to-end project leadership.
• Collaboration with a distributed team across Europe and the Americas.
• Exposure to satellite imagery, geospatial data, CV, and large-scale ML systems.
• Challenging technical problems with real-world impact.