Overstory

Overstory

Overstory uses AI and satellite imagery to prevent wildfires and power outages by analyzing vegetation for electric utilities.

Utilities
11-50
Founded 2018
$25M raised

Description

  • Architect and build advanced machine learning 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 machine learning systems, tooling, and processes to keep models state-of-the-art and maintainable.
  • Collaborate with MLOps peers to streamline training, inference, and monitoring in production environments.
  • Mentor other engineers and drive architectural decisions and engineering standards across the modeling organization.

Requirements

  • 10+ years of experience designing and building production-grade machine learning pipelines and systems, with strong candidates considered at 6+ years.
  • Strong background in deep learning, computer vision, or remote sensing.
  • Experience designing end-to-end ML systems from data ingestion and preprocessing through deployment and monitoring.
  • Hands-on experience with frameworks such as PyTorch, TensorFlow, XGBoost, or LightGBM.
  • Experience with data tools such as 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.
  • Comfort leading architectural discussions and mentoring other engineers.
  • Must be based in the US or Canada.
  • Time zone alignment required: Eastern North America (NST, AST, EST).
  • Preferred experience in wildfire science, forestry, or remote sensing.
  • Preferred experience integrating physics-based models with ML, active learning, or uncertainty quantification.
  • Preferred experience with model interpretability and data provenance for environmental ML systems.
  • Preferred experience with deep learning models for weather or climate data.
  • Preferred experience working in remote-first or globally distributed teams.

Benefits

  • Competitive salary with equity.
  • Flexible working environment with a high degree of autonomy.
  • Remote working budget.
  • Educational budget and time to develop new skills.
  • Mission-driven work focused on reducing wildfires and supporting climate resilience.
  • A collaborative, open, and respectful team culture.
  • Occasional in-person collaboration and an annual team gathering.

Interested in this position?

Apply directly on the company website

Apply Now

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