Staff Machine Learning Engineer - Wildfire

Overstory; Netherlands; Remote; EUR 120,000 - 180,000; Full time

Benefits offered by this job

Home office stipend

Coworking budget

Ongoing education allowances

Mission‑driven work culture

Mission-driven work

Job summary

Overstory is seeking a Staff Machine Learning Engineer in the Netherlands to lead the development and scaling of wildfire fuel detection models. You will work with data scientists, ML engineers, and product teams to ensure accuracy, robustness, and production readiness, balancing scientific rigor with engineering excellence.

You will mentor other engineers, drive architectural decisions, and define modeling and deployment standards across Overstory.

Qualifications

• 10+ years of experience designing and building production‑grade ML pipelines and systems.
• Background in wildfire science, forestry, or remote sensing or related environmental domains.
• Strong experience with deep learning, computer vision, or remote sensing.
• End‑to‑end ML system design: data ingestion, preprocessing, deployment, monitoring.
• Experience with PyTorch or TensorFlow and data tools like Dask, Spark, GeoPandas.
• Familiarity with cloud ML platforms (GCP Vertex AI) and scalable infrastructure.
• Excellent collaboration and mentoring abilities across technical and scientific teams.

Responsibilities

• Architect and build advanced ML models to map vegetation and fuel conditions across geographies.
• Design and maintain robust data and feature pipelines for large-scale geospatial data.
• Collaborate with wildfire science and product teams to define objectives and evaluation metrics.
• Build reproducible experimentation frameworks and model evaluation workflows.
• Scale models from research to production with focus on performance and reliability.
• Lead evolution of ML systems, tooling, and processes for maintainable wildfire fuelscape models.
• Collaborate with MLOps to streamline training, inference, and monitoring in production environments.

Skills

Senior leadership

ML systems design

Geospatial ML

Production ML pipelines

Communication

Mentoring

Tools

PyTorch

TensorFlow

XGBoost

LightGBM

Dask

Spark

GeoPandas

Vertex AI / GCP

Job description

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

• 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
• You have a background in wildfire science, forestry, or remote sensing
• 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

Nice To Have

• 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

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis