Senior Geospatial ML Engineer building satellite-imagery vegetation intelligence for a climate-tech company. Improving production models and pipelines to help utilities prevent wildfires and outages.
Responsibilities
Develop new vegetation intelligence products using geospatial Python libraries, machine learning, and deep learning techniques
Maintain and improve existing products through data exploration, model optimization, and debugging
Lead projects end-to-end from planning and execution through delivery
Communicate the value of work to cross-functional stakeholders across the organization
Build measurement frameworks and tooling to evaluate model performance
Guide data-driven decisions about where to focus impact
Collaborate with upstream data ingestion teams and downstream product delivery teams to shape platform architecture and pipelines
Requirements
5+ years of experience as a Machine Learning Engineer or Data Scientist building and deploying production ML/deep learning models
Demonstrated experience building computer vision or deep learning models on satellite or aerial imagery
Proficiency with geospatial Python libraries such as rasterio, geopandas, shapely, and GDAL
Proficiency with geospatial data formats
Eligible to work without visa sponsorship; no visa sponsorship is available
Experience with Python-based ML/deep learning frameworks such as PyTorch, TensorFlow, and scikit-learn
Experience with data pipeline orchestration tools such as Dagster, Airflow, or dbt, or equivalent workflow management systems
Experience with QGIS or equivalent geospatial visualization and analysis software
Experience with model monitoring, evaluation metrics, and performance measurement in production environments
Experience with multi-spectral or hyperspectral satellite imagery data is nice to have
Background in vegetation analysis, forestry, agriculture, or environmental monitoring applications is nice to have
Experience with monitoring and observability tools such as Grafana, Sentry, or Prometheus is nice to have
Track record of leading cross-functional projects or initiatives from planning through delivery is nice to have
Benefits
Fully remote work arrangement
Opportunity to make a direct, measurable impact on grid resilience and climate action
Mission-driven climate-tech work focused on wildfire prevention and power outage prevention
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