Visiting Scientist

The position involves developing and implementing geospatial foundation models using satellite imagery to analyze environmental changes and natural disasters, bridging academic research with operational AI solutions at Planet.

• Develop and train proprietary geospatial foundation models optimized for Planet imagery, focusing on time-series data integration.
• Evaluate existing foundation model architectures to identify performance issues and transferability.
• Build workflows for detecting short-lived environmental events such as floods and fires using high-cadence embeddings.
• Integrate multi-sensor data sources, including Planet Scope, Sentinel-1 SAR, and others, to maintain time-series continuity under cloud cover.
• Collaborate with research scientists to transition prototypes into scalable, operational AI/ML products.

• A recently completed PhD in Geospatial Analytics, Computer Science, Remote Sensing, or a 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 such as PyTorch and Tensor Flow.
• Expert-level Python skills and proficiency with the geospatial scientific stack, including xarray, Dask, Rasterio, and Geo Pandas.
• Experience building automated pipelines for preprocessing and labeling planetary-scale datasets.
• Experience working within a research lab environment and a strong desire to apply academic rigor to industry challenges.

Health Savings Account (HSA) with a company contribution

Generous Paid Time Off in addition to holidays and company-wide days off

16 Weeks of Paid Parental Leave

Wellness Program and Employee Assistance Program (EAP)

Home Office Reimbursement

Monthly Phone and Internet Reimbursement

Tuition Reimbursement and access to Linked In Learning

Equity

Commuter Benefits if local to an office

Discretionary short-term and long-term incentives (bonus and equity)