Senior Geospatial Machine Learning Engineer

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

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