Senior Geospatial Machine Learning Engineer

Stack

Responsibilities

• ▹Develop new vegetation intelligence products using geospatial Python libraries, machine learning and deep learning
• ▹Support existing products through data exploration, model improvements, and bug fixes (QGIS, Dagster, Sentry, Grafana)
• ▹Lead projects end-to-end, from planning to delivery, communicating value to stakeholders
• ▹Build tooling and processes to measure team performance and business value
• ▹Collaborate closely with upstream data ingestion and downstream delivery teams
• ▹Contribute to shaping team culture and technical direction

Requirements

• ▹8-10+ years of relevant experience in machine learning or geospatial engineering
• ▹Strong Python proficiency with geospatial libraries: GDAL, Rasterio, Shapely, Fiona, GeoPandas
• ▹Experience with scientific Python tools: NumPy, SciPy, scikit-learn, Pandas
• ▹Hands-on experience with deep learning frameworks: PyTorch and/or TensorFlow
• ▹Experience with satellite or aerial imagery and raster/vector geospatial datasets
• ▹Experience with workflow orchestration tools (e.g. Dagster)
• ▹Ability to lead projects independently and communicate technical work to non-technical stakeholders

Nice to have

• ▹Familiarity with vegetation science, forestry, or utility/energy infrastructure domains
• ▹Experience with observability tooling such as Sentry or Grafana
• ▹Background at a climate tech, geospatial AI, or remote sensing company

What we offer

• ▹Fully remote work

About the company

A fast-growing, mission-driven climate tech company using AI and advanced satellite imagery to help electric utilities manage vegetation risks, preventing wildfires and reducing outages.