Staff Machine Learning Engineer - Wildfire

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.

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.

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.

• You thrive at the intersection of machine learning, geospatial data, and environmental science, and are motivated by the opportunity to reduce wildfire risk through data-driven insights.
• You love working in a remote-first, fast-moving environment where collaboration and adaptability are essential.
• 10+ years of experience designing and building production-grade ML pipelines and systems – but don’t filter yourself out if you feel you’re a strong candidate with 6+ years.
• 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 communication skills and ability to collaborate across technical and scientific domains.
• Comfortable leading architectural discussions and mentoring other engineers.
• You are based in the US or Canada.

• Background in wildfire science, forestry, or remote sensing.
• Experience integrating physics-based models with ML or working with active learning and uncertainty quantification.
• Experience in model interpretability and data provenance for environmental ML systems.
• Experience with deep learning models for weather or climate data.
• Experience in remote-first or globally distributed teams.

• 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.