Visiting Scientist

• Contribute to the design and training of a foundation model optimized for Planet imagery, focusing on time-series data integration.
• Execute systematic evaluation of existing GFM architectures against PlanetScope data to identify performance bottlenecks.
• Build and test workflows for detecting short-lived events (e.g., floods, fires) using high-cadence embeddings.
• Develop methods for multi-sensor data fusion to maintain time-series continuity under cloud cover.

This role advances Planet's mission to use space data for environmental and humanitarian benefit by developing AI models that detect rapid changes like floods and fires, enabling faster disaster response and better environmental monitoring.

• Recently completed PhD in Geospatial Analytics, Computer Science, Remote Sensing, or related field.
• Demonstrated experience in building AI-based models for environmental change or satellite image analysis.
• Hands-on experience with foundation models, contrastive learning, and deep learning frameworks (PyTorch/TensorFlow).
• Expert-level Python skills and proficiency with geospatial scientific stack (xarray, Dask, Rasterio, GeoPandas).

Comprehensive Medical, Dental, and Vision plans; Health Savings Account with company contribution; Generous Paid Time Off; 16 Weeks Paid Parental Leave; Wellness Program; Home Office Reimbursement; Monthly Phone/Internet Reimbursement; Tuition Reimbursement; Equity; Commuter Benefits; Volunteering PTO. US base salary range: $144,500 - $180,600 USD.

Planet designs, builds, and operates the largest constellation of imaging satellites, delivering unprecedented Earth observation data to commercial, environmental, and humanitarian sectors.