About the Role:

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 ephemeral 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 PlanetScope data.

Impact You'll Own:

• 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., TerraMind, Prithvi, Clay) against PlanetScope 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 PlanetScope, 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 PlanetScope'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.

What You Bring:

• 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, PlanetScope, Sentinel-1) and high-resolution mapping at varying scales (3m, 10m, 30m).
• Technical Proficiency: Expert-level Python skills and experience with the scientific stack (xarray, Dask, NumPy, Rasterio, GeoPandas) and deep learning frameworks.
• Scale-Minded Research: Experience building automated pipelines for preprocessing and labeling planetary-scale datasets.
• Collaborative Spirit: A history of leading research labs and a desire to work in a fast-paced, industrial R&D environment.

What Makes You Stand Out:

• Specialized Environmental Research: Extensive experience specifically in flood damage quantification and methane-related water dynamics.
• Proven Funding & Publication Record: History of leading NASA-funded or similar high-impact geospatial research projects.
• Architectural Knowledge: Direct experience fine-tuning or modifying specific GFM architectures like TerraMind or Prithvi.

Hybrid Experience: A mix of deep academic rigor and the ability to prototype rapid-change monitoring tools for operational readiness.

Application Deadline:

August 11, 2026 by 11:59p / 23:59 CET (Central European Time)

Benefits While Working at Planet:

These offerings are dependent on employment type and geographical location, based upon applicable law or company policy.

• 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)
• Volunteering Paid Time Off

Compensation:

The US base salary range for this full-time position at the commencement of employment is listed below. Additionally, this role might be eligible for discretionary short-term and long-term incentives (bonus and equity). The final salary range is determined by job related experience, skills and location. The range displays our typical hiring range for new hire salaries in US locations only. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

San Francisco Salary Range

$231,500-$289,400 USD

San Francisco Fair Chance OrdinancePursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.