Visiting Staff Scientist

The role involves leading the development of proprietary geospatial foundation models using satellite imagery to analyze dynamic Earth events, integrating multi-sensor data, and advancing AI research in remote sensing within a collaborative, innovative environment. Key Responsibilities Lead the development of Planet's proprietary geospatial foundation models (GFMs) trained on Planet imagery Research and create high-cadence, temporally dense embeddings capturing dynamic Earth events Evaluate and benchmark existing GFMs against PlanetScope data for performance and transferability Design embeddings and workflows for detecting short-lived, high-impact events such as floods and fires Explore multi-sensor data integration to ensure robust time-series analysis under various conditions Develop active learning workflows to optimize labeling and reduce annotation efforts for time-sensitive mapping Publish research findings and present at industry conferences to showcase Planet's AI advancements Oversee technical development and transition of prototypes into operational geospatial products Requirements PhD and current Faculty Professor status in Geospatial Analytics, Computer Science, Remote Sensing, or a related field. 12 years of experience in remote sensing and satellite image analysis, with a proven track record in building AI-based models for environmental change such as flood-extent and water dynamics. Extensive experience with foundation models, contrastive learning (CLIP-like models), and multi-model vision-language models (MMVLMs). Proficiency in multi-sensor integration including Landsat, Sentinel-2, PlanetScope, Sentinel-1, and high-resolution mapping at varying scales of 3m, 10m, and 30m. Expert-level Python skills and experience with the scientific stack including xarray, Dask, NumPy, Rasterio, GeoPandas, and deep learning frameworks. Experience building automated pipelines for preprocessing and labeling planetary-scale datasets. A history of leading research labs and a desire to work in a fast-paced, industrial R&D environment. Proven funding through leading NASA-funded or similar high-impact geospatial research projects. Direct experience fine-tuning or modifying specific GFM architectures like TerraMind or Prithvi. Comprehensive Medical, Dental, and Vision plans 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 LinkedIn Learning Equity Commuter Benefits if local to an office Discretionary short-term and long-term incentives bonus and equity Salary range: 231,500 - 289,400 USD (for San Francisco location) #J-18808-Ljbffr NextGenEnergyJobs