Visiting Staff Scientist

Planetlabs; San Francisco (CA); Hybrid; USD 231,500 - 289,400; Full time

Benefits offered by this job

Comprehensive Medical, Dental, and Vision plans

Generous Paid Time Off

Job summary

Planetlabs in San Francisco is seeking a Visiting Staff Scientist for a one-year sabbatical in its AI Research team. You will lead the development of proprietary geospatial foundation models and design workflows for detecting high-impact environmental events.

The ideal candidate holds a PhD with deep domain expertise in remote sensing, and a history of publishing impactful research. Comprehensive benefits and competitive salary range of $231,500 – $289,400 are offered.

Qualifications

• PhD and current Faculty/Professor status in Geospatial Analytics, Computer Science, or related field.
• 12+ years of experience in remote sensing and satellite image analysis.
• Extensive experience with foundation models and deep learning frameworks.

Responsibilities

• Lead the development of proprietary geospatial foundation models.
• Design workflows for detecting high-impact events.
• Publish findings in top-tier journals and present at academic conferences.

Skills

Remote sensing

AI model development

Geospatial analytics

Python

Education

PhD in Geospatial Analytics or related field

Tools

xarray

Dask

NumPy

Rasterio

GeoPandas

Job description

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).

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

• 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

EEO statement

Planet is committed to building a community where everyone belongs and we invite people from all backgrounds to apply. Planet is an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws.