Geospatial Machine Learning Engineer

Staff Geospatial Machine Learning Engineer

The climate crisis is the defining challenge of our time— but it’s also the greatest opportunity for innovation, and a challenge we’re proud to take on. At Overstory, we’re harnessing cutting‑edge technology to enable a resilient electrical grid that keeps communities thriving as our world changes.

The grid is the backbone of life as we know it. It powers hospitals, keeps food fresh, and ensures communities stay connected. But extreme weather, aging infrastructure, and growing wildfire risks are putting this critical system under pressure. All of this combined makes the electric utility industry the greatest opportunity for tackling climate change.

One of the leading causes of catastrophic wildfires and power outages? Trees and brush coming into contact with power lines.

That’s where we help. At Overstory, we use AI and advanced satellite imagery to pinpoint and prioritize vegetation risks before they materialize. By giving utilities critical analysis on those risks, we’re helping prevent outages, reduce wildfire risks, and accelerate the transition to a safer, more resilient grid.

Our team spans the Americas and Europe, and we work with utility partners across the Americas and beyond. We’re outdoor enthusiasts, musicians, artists, athletes, parents, and adventurers—15 nationalities strong and growing. What unites us is a passion for solving complex problems, a commitment to climate action, and the belief that technology should be a force for good.

Join us to help us build a more resilient world together.

We are looking for a Staff Geospatial MLE to join the Vegetation Modeling team ’ll spend most of your time working within small groups on our team to experiment with, build, and improve algorithms for understanding how vegetation impacts our customers. In the past, we’ve developed solutions to coregister imagery, locate critical energy infrastructure, and identify tree species, heights, and health.

Right now, we split our time between maintaining and improving these solutions and developing new features to understand wildfire risk and assess the impact of different management strategies.

On our team, you’ll generally be working with satellite imagery and other geospatial datasets, and using machine learning or deep learning to analyze their contents. You’ll be regularly interfacing with our data and models through Python code, QGIS projects, and Dagster pipelines. You’ll thrive if you enjoy working with a cross‑functional group of product, design, engineering, and platform team members, and being involved throughout the full scientific product lifecycle.

As a quickly‑growing, early‑stage startup, you’ll also be able to make significant contributions to the direction and culture of our organization. We collaborate closely with upstream teams responsible for ingesting data, and downstream teams that further refine or deliver those outputs to customers. You’ll be able to help shape how we work within our team and across the organization, influence how we make core decisions about our platform and pipelines, and scope out impactful projects.

• Develop new vegetation intelligence products using standard geospatial Python libraries, as well as machine learning and deep learning tools
• Support existing products through data exploration, model improvements, and bugfixes, especially using QGIS, Dagster, Sentry, and Grafana
• Represent the team by leading projects and initiatives, being responsible for planning, execution, delivery, and ensuring the value of our contributions is clear to other stakeholders throughout the organization
• Build the tooling and processes necessary to measure the value and performance of our contributions, and help to make data‑driven decisions about where we can have the greatest impact

• At least 10 years of commercial experience as a Data Scientist or Machine Learning Engineer
• Advanced scientific Python experience, including numpy, scipy, scikit‑learn, pandas
• Experience with geospatial or satellite data, and tooling such as gdal, rasterio, shapely, fiona, geopandas, QGIS
• Experience with deep learning algorithms,…