Staff ML Engineer — Wildfire & Geospatial AI Leader

Overstory; United States; Remote; USD 190,000 - 270,000; Full time

Benefits offered by this job

Location-specific compensation

Home office stipend

Flexible, autonomous work environment

Education budgets

Job summary

Overstory is seeking a Staff Machine Learning Engineer to lead development and scaling of wildfire fuel detection models using satellite and environmental data. You will shape modeling capabilities, balance scientific rigor with engineering excellence, and mentor engineers across the team.

Reporting to the VP of Product Engineering, you’ll collaborate with data scientists, ML engineers, and product teams to ensure models are accurate, robust, and production-ready.

Qualifications

• 10+ years designing and building production-grade ML pipelines and systems.
• Background in wildfire science, forestry, or remote sensing is noted in nice-to-have sections.
• Strong experience with geospatial data and environmental science contexts.

Responsibilities

• Architect and scale ML models for vegetation and fuel mapping across geographies.
• Design robust data and feature pipelines for large-scale geospatial data.
• Collaborate with science and product teams to define modeling objectives and metrics.
• Build reproduction-focused experimentation and evaluation workflows.
• Scale models from research to production with reliability and explainability.
• Lead ML system architecture discussions and mentor engineers.

Skills

Geospatial ML

Production ML pipelines

Deep learning

PyTorch

TensorFlow

XGBoost/LightGBM

GeoPandas/Spark/Dask

Vertex AI / GCP

Leadership & mentoring

Communication

Tools

GeoPandas

Spark

Dask

Vertex AI

Job description

Overstory is seeking a Staff Machine Learning Engineer to lead development and scaling of wildfire fuel detection models using satellite and environmental data. You will shape modeling capabilities, balance scientific rigor with engineering excellence, and mentor engineers across the team.

Reporting to the VP of Product Engineering, you’ll collaborate with data scientists, ML engineers, and product teams to ensure models are accurate, robust, and production-ready.