About the Role
Join a mission-driven, AI-powered climate tech company using advanced satellite imagery to help utilities prevent wildfires and power outages by identifying vegetation risks before they become critical. As a Senior Geospatial Machine Learning Engineer on the Vegetation Modeling team, you'll develop and improve ML solutions that analyze geospatial data and satellite imagery at scale — making a direct impact on grid resilience and climate action. The team spans the Americas and Europe, and this role is fully remote.
What You'll Do
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 using tools such as QGIS, Dagster, Sentry, and Grafana.
Lead projects end-to-end — from planning and execution through delivery — and communicate the value of your work to cross-functional stakeholders across the organization.
Build measurement frameworks and tooling to evaluate model performance and 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.
What We're Looking For
Required (Dealbreakers):
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 (e.g.,
rasterio,geopandas,shapely,GDAL) and geospatial data formats.
Required Skills:
Experience with Python-based ML/deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Experience with data pipeline orchestration tools (e.g., Dagster, Airflow, 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.
Nice to Have:
Experience working with multi-spectral or hyperspectral satellite imagery data.
Background in vegetation analysis, forestry, agriculture, or environmental monitoring applications.
Familiarity with monitoring and observability tools (e.g., Grafana, Sentry, Prometheus).
Experience leading cross-functional projects or initiatives from planning through delivery.
Passion for climate action and applying technology to complex, real-world environmental problems.
Compensation & Benefits
Compensation details were not provided for this role. A competitive package commensurate with experience is expected for a senior-level position at a well-funded climate tech company.
Location
Work arrangement: Fully remote
Eligible locations: Canada, United States, and select European countries
Visa sponsorship: Not available — candidates must have existing work authorization
