Design, build, and operate production-grade geospatial machine learning models
Uncover hidden geothermal systems and drive real-world exploration decisions
Collaborate with research, engineering, geoscience, land, and field teams
Serve as a hands-on contributor and technical leader
Grow deep learning expertise across teams
Requirements
6+ years professional experience in machine learning engineering, preferably in a business environment
Deep expertise in modern deep learning and statistical methods
Proven experience developing, deploying, and maintaining production-grade machine learning models
Strong software and infrastructure fluency. Our tech stack includes Python, SQL, PyTorch, GitHub, and Docker. (Familiarity with GCP, Dagster, Terraform, and QGIS is a plus.)
Ability to work closely and collaboratively with engineers, domain experts, and non-technical stakeholders
Strong plus: computer vision expertise; experience with geospatial, remote sensing, or geophysical data
Tech Stack
Docker
Google Cloud Platform
Python
PyTorch
Remote Sensing
SQL
Terraform
Benefits
Paid holidays
15 days PTO + PTO accrual increase based on tenure
Medical, dental, and vision coverage
401k
Stock options
Growth opportunities at a company with a direct impact in displacing carbon emissions