Senior Geospatial Machine Learning Engineer
Tasks
- Collaborate with cross functional teams to deliver model performance and impact
- Develop and deploy vegetation intelligence products using machine learning
- Develop measurement frameworks evaluation tooling and performance metrics
- Explore geospatial datasets and optimize production models
- Influence data pipelines processing workflows and platform architecture
- Integrate geospatial ML outputs into customer solutions
- Lead technical projects end to end from planning to delivery
- Maintain and enhance vegetation modeling products
- Monitor production models and investigate performance issues
- Use QGIS to analyze data and diagnose issues
Perks/Benefits
- Climate technology mission impact
- Distributed team collaboration
- Fully Remote Working Environment
- Meaningful technical ownership
- Project leadership opportunities
Skills/Tech-stack
Airflow | Computer Vision | DBT | Dagster | Data Pipelines | Deep learning | GDAL | Geopandas | Geospatial Data | Geospatial visualization | Grafana | Hyperspectral Satellite Imagery | Machine Learning | Model Evaluation | Model Monitoring | Multispectral satellite imagery | Observability | Prometheus | PyTorch | Python | QGIS | Rasterio | Satellite imagery | Scikit-learn | Sentry | Shapely | TensorFlow
Education
N/A
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