Visiting Staff Scientist

Welcome to Planet. We believe in using space to help life on Earth.

Planet designs, builds, and operates the largest constellation of imaging satellites in history. This constellation delivers an unprecedented dataset of empirical information via a revolutionary cloud‑based platform to authoritative figures in commercial, environmental, and humanitarian sectors. We are both a space company and data company all rolled into one.

Customers and users across the globe use Planet's data to develop new technologies, drive revenue, power research, and solve our world's toughest obstacles.

As we control every component of hardware design, manufacturing, data processing, and software engineering, our office is a truly inspiring mix of experts from a variety of domains.

We have a people‑centric approach toward culture and community and we strive to iterate in a way that puts our team members first and prepares our company for growth. Join Planet and be a part of our mission to change the way people see the world.

Planet is a global company with employees working remotely worldwide and joining us from offices in San Francisco, Washington DC, Germany, Austria, Slovenia, and The Netherlands.

We are seeking a distinguished Visiting Staff Scientist to join our AI Research (AIR) team for a one‑year sabbatical residency. In this role, you will play a pivotal part in our mission to create a "Queryable Earth" by leading the development of Planet's proprietary geospatial foundation models (GFMs).

While Planet has historically leveraged external models like Google's RSFM and RemoteCLIP, we are now focused on building in‑house models specifically trained on our unique imagery. You will lead research into creating temporally dense embeddings that go beyond static annual summaries, capturing the dynamic and fleeting nature of our planet—from rapid flooding to disaster impacts.

You will collaborate with a multi‑disciplinary team of "Planeteers" across space operations, data pipelines, and analytics to co‑develop AI/ML solutions that leverage the high spatial resolution and near‑daily revisit of Planet Scope data.

• Develop Planet's Proprietary GFM: Lead the research and development of a foundation model specifically trained on Planet imagery, incorporating the time‑axis to create high‑cadence time‑series embeddings.
• Benchmark Geospatial Architectures: Systematically evaluate and compare existing GFMs (e.g., Terra Mind, Prithvi, Clay) against Planet Scope data to assess performance, computational cost, and transferability.
• Capture Dynamic Earth Events: Design embeddings and workflows optimized for detecting short‑lived, high‑impact events such as floods, rapid surface‑water expansion, and fire.
• Multi‑Sensor Integration: Explore the synergy between Planet Scope, Sentinel‑1 SAR, and other commercial SAR data to ensure robust time‑series analysis even under cloud cover.
• Human‑in‑the‑Loop Innovation: Use embeddings to design active learning workflows that prioritize labeling and reduce the annotation burden for time‑sensitive mapping tasks.
• Academic & Technical Leadership: Publish findings in top‑tier journals and present at conferences (e.g., IGARSS, CVPR), highlighting Planet Scope's unique value in the foundation model ecosystem.
• Mentor & Collaborate: Oversee the technical direction of a dedicated postdoc and collaborate with Planet's research scientists to transition prototypes into operational products.

• Distinguished Academic Background: PhD and current Faculty/Professor status in Geospatial Analytics, Computer Science, Remote Sensing, or a related field.
• Deep Domain Expertise: 12+ years of experience in remote sensing and satellite image analysis, with a proven track record in building AI‑based models for environmental change (e.g., flood‑extent, water dynamics).
• Multimodal AI Fluency: Extensive experience with foundation models, contrastive learning (CLIP‑like models), and multi‑model vision‑language models (MMVLMs).
• Advanced Geospatial Toolkit: Proficiency in multi‑sensor integration (Landsat, Sentinel‑2, Planet Scope, Sentinel‑1) and high‑resolution mapping at varying scales (3m, 10m,…