Staff Machine Learning Engineer - Wildfire at Overstory

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Full Time

Start Date

Immediate

Expiry Date

27 Jan, 26

Salary

0.0

Posted On

30 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Geospatial Data, Environmental Science, Deep Learning, Computer Vision, Remote Sensing, Data Ingestion, Preprocessing, Deployment, Monitoring, PyTorch, TensorFlow, XGBoost, LightGBM, Dask, Spark, GeoPandas

Industry

Software Development

Description

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. The role 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. 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. About you 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 ET → PT time zones. Nice-to-haves 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. 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 85 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, France, Sweden, Denmark, Switzerland, 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. Diversity & Inclusion We place enormous value on diversity and inclusion and strive to continually bring in people of all genders, races, creeds, ethnicities, abilities and backgrounds. We believe that the best ideas emerge when people with different perspectives and approaches work together on a problem. We’re always looking to diversify our team further, but we’re proud of the fact that four out of the nine people on our leadership team are female, 46% of the overall team are female and 20% of the team are people of color. Our team speaks fifteen languages: English, Dutch, French, Spanish, German, Italian, Portuguese, Russian, Luxembourgish, Lithuanian, Bulgarian, Cantonese, Estonian, Danish and Korean. Our values Tackling the climate crisis is our greatest mission. We act with urgency. Our curiosity fuels our growth. We recognize that change is constant, and we find joy and power in exploration. We’re rooted in diversity. Just as ecosystems need biodiversity to thrive, our resiliency comes from our differences. We care for each other. We love the power of machines but we nurture each other as humans. Trust is fundamental. We assume the best in everyone, and we share ideas openly so that we have a positive impact. _________________________________ Use of AI in Our Hiring Process We sometimes use AI tools to support parts of our hiring process, such as helping us manage applications more efficiently or ensuring job descriptions are clear and inclusive. But don’t worry, all hiring decisions are always made by people, not machines. Any data processed by AI is handled securely in line with GDPR and our Privacy Notice.

Responsibilities

Lead the development and scaling of the Wildfire Fuel Detection Model, focusing on understanding vegetation structure and wildfire risk. Collaborate with data scientists and product teams to ensure models are accurate and production-ready.