Senior Geospatial ML 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 Originally posted on [Himalayas](https://himalayas.app)