Senior Geospatial Machine Learning Engineer
Technology, Information and Internet · 2-10 employees
About the role
Develop and improve machine learning solutions for analyzing geospatial data and satellite imagery to identify vegetation risks. Lead end-to-end projects while collaborating with cross-functional teams to build scalable platform architecture and measurement frameworks.
What they look for
Requirements
Requires 5+ years of experience in machine learning or data science with a focus on computer vision or deep learning models applied to satellite imagery. Proficiency in geospatial Python libraries and experience with production-level ML pipelines are essential.
Full description
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
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