Senior Geospatial Machine Learning Engineer

About this role

ABOUT THE ROLE

Join the Vegetation Modeling team at a mission-driven climate-tech company that uses AI and 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, you'll develop and improve ML solutions that analyze geospatial data and satellite imagery — making a direct, measurable 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 like 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 throughout 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.

- Eligible to work without visa sponsorship — no visa sponsorship is available for this role.

Required skills & experience:

- Experience with Python-based ML/deep learning frameworks (e.g., PyTorch, TensorFlow, 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.

- Experience with monitoring and observability tools (e.g., Grafana, Sentry, Prometheus).

- Track record of leading cross-functional projects or initiatives from planning through delivery.

LOCATION & WORK ARRANGEMENT

This is a fully remote role. The team operates across multiple time zones in the Americas and Europe. Candidates based in Canada are preferred for this posting.

⚠️ Visa sponsorship is not available. Applicants must be authorized to work in their country of residence.

TECH STACK

- Languages & Libraries: Python, NumPy, SciPy, Pandas, scikit-learn, PyTorch, TensorFlow

- Geospatial: GDAL, rasterio, shapely, fiona, geopandas, QGIS

- Pipelines & Orchestration: Dagster (or similar — Airflow, dbt)

- Monitoring & Observability: Grafana, Sentry, Prometheus