Senior Geospatial Machine Learning Engineer
Tasks
- Build evaluation tooling and performance metrics
- Communicate model performance and business impact
- Develop and deploy vegetation intelligence products
- Explore geospatial datasets and improve models
- Influence data pipelines and platform architecture
- Integrate geospatial ML outputs into products
- Lead technical projects end-to-end
- Maintain vegetation modeling products
- Monitor production models and troubleshoot issues
- Use workflow and monitoring tools to diagnose issues
Perks/Benefits
- Climate technology mission impact
- Distributed team collaboration
- Fully remote
- High-impact technical challenges
- Ownership of machine learning products
Skills/Tech-stack
Aerial Imagery | Airflow | Computer Vision | Computer Vision Model Development | DBT | Dagster | Data Pipelines | Deep learning | GDAL | Geopandas | Geospatial Data | Geospatial Python | Geospatial Python libraries | Grafana | Hyperspectral Imaging | Model Development | Model Evaluation | Model Monitoring | Multispectral imaging | Observability | Prometheus | PyTorch | Python | Python libraries | QGIS | Rasterio | Risk Modeling | Satellite imagery | Scikit-learn | Sentry | Shapely | TensorFlow | Vegetation analysis | Wildfire risk modeling
Education
N/A
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