Staff Machine Learning Engineer - Wildfire

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. 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. Role & Team As a Staff Machine Learning Engineer at Overstory, you will lead the development and scaling of our Wildfire Fuel Detection Model. This core engine powers how we understand vegetation structure, fuel loads, and wildfire risk from satellite and environmental data. You’ll help shape the next generation of Overstory’s modeling capabilities by combining cutting-edge ML techniques, large-scale geospatial data, and real-world domain expertise. Reporting to our VP of Product Engineering, you’ll work closely with data scientists, ML engineers, and product teams to ensure our wildfire models are accurate, robust, and production-ready – balancing scientific rigor with practical engineering excellence. As a senior technical leader, you’ll mentor other engineers, drive architectural decisions, and define standards for modeling, experimentation, and deployment across Overstory. Time zone requirement: Eastern North America (NST, AST, EST) What You’ll Do In collaboration with data, ML, and science colleagues, you will: Architect and build advanced ML models to map and predict vegetation and fuel conditions across diverse geographies. Design and maintain robust data and feature pipelines for large-scale geospatial and temporal data. Partner with wildfire science and product teams to define modeling objectives and evaluation metrics tied to real-world impact. Build reproducible experimentation frameworks and model evaluation workflows. Scale models from research to production with a focus on performance, reliability, and explainability. Lead the evolution of ML systems, tooling, and processes — ensuring that our wildfire fuelscape models remain state-of-the-art and maintainable. Collaborate with MLOps peers to streamline training, inference, and monitoring in production environments. Skills & Experience Experience thriving at the intersection of machine learning, geospatial data, and environmental science; deeply motivated by the opportunity to reduce wildfire risk through data-driven insights 10+ years of experience designing and building production-grade ML pipelines and systems Strong background in deep learning, computer vision, or remote sensing Skilled in designing end-to-end ML systems — from data ingestion and preprocessing to deployment and monitoring Hands-on experience with frameworks like PyTorch, TensorFlow, XGBoost, or LightGBM, and data tools like Dask, Spark, or GeoPandas Familiarity with GCP and Vertex AI, or similar cloud-based ML platforms Strong c