Senior Geospatial Machine Learning Engineer

We are looking for a Senior Geospatial MLE to join the Vegetation Modeling team at Overstory. You’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.

What you’ll do

• 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

About you

• At least 8 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, especially as applied to geospatial data, and tooling such as pytorch, tensorflow
• Experience leading small teams organized around projects or initiatives
• Passionate about climate
• Enjoy working in a remote first, fast-moving environment.
• You are based in the GMT/ CET time zone. Open to US ET for those that are able to have significant overlap with GMT/ CET working hours. 

Nice-to-haves

• Experience at early-stage startups and remote-first organizations
• An understanding of the challenges of working with geospatial data at scale, as well as possible solutions to those challenges
• Deep industry experience in a unique geospatial or forest science domain, such as working with SAR imagery or developing and supporting wildfire products

What you get

• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis.
• Flexible working environment with a lot of autonomy. We build our work days around our lives, not the other way around.
• Other benefits like a remote working budget, an educational budget and time to develop new skills.
• To be surrounded by an excellent, vibrant, smart team who have each other's back and believe in a culture of openness, tolerance and respect.
• Equity and a competitive salary.

About our team 

We are a group of 62 people from all over the world. Fifteen nationalities are represented in our team. We work remotely from nine different countries and we are looking for candidates that are also living and working in one of these countries: United States, the Netherlands, United Kingdom, Ireland, Estonia, Portugal, Spain, France, Sweden and Canada. We meet up once a year in-person for our unforgettable team gathering event. We also offer the option to occasionally meet up for in-person collaboration.