Planet

space

VisitingStaffScientist

$232–289k San Francisco, California, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Visiting Staff Scientist at Planet. Skills: geospatial foundation models (GFMs), time-series embeddings, contrastive learning, multi-model vision-language models (MMVLMs), multi-sensor integration, Python, deep learning frameworks. 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. Systematically evaluate and compare existing GFMs against PlanetScope data to assess performance,”

What You'll Achieve.

create a “Queryable Earth”; Develop Planet’s Proprietary GFM; Benchmark Geospatial Architectures; Capture Dynamic Earth Events; Multi-Sensor Integration; Human-in-the-Loop Innovation; Academic & Technical Leadership; Mentor & Collaborate; transition prototypes into operational products

Industry & Context.

space
Problems you'll solve

solve our world’s toughest obstacles; building AI-based models for environmental change; design embeddings and workflows optimized for detecting short-lived, high-impact events; explore the synergy between PlanetScope, Sentinel-1 SAR, and other commercial SAR data to ensure robust time-series analysis even under cloud cover; design active learning workflows that prioritize labeling and reduce the annotation burden for time-sensitive mapping tasks

Eligibility Requirements

one-year sabbatical residency

What They're Looking For.

Must Have

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, Proven track record in building AI-based models for environmental change, Expert-level Python skills, Experience with the scientific stack (xarray, Dask, NumPy, Rasterio, GeoPandas), Experience with deep learning frameworks, Experience building automated pipelines for preprocessing and labeling planetary-scale datasets

Nice to Have

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, Direct experience fine-tuning or modifying specific GFM architectures like TerraMind or Prithvi, A mix of deep academic rigor and the ability to prototype rapid-change monitoring tools for operational readiness

What You'll Do.

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

Systematically evaluate and compare existing GFMs against PlanetScope data to assess performance

Design embeddings and workflows optimized for detecting short-lived

high-impact events such as floods

rapid surface-water expansion

Explore the synergy between PlanetScope

and other commercial SAR data to ensure robust time-series analysis even under cloud cover

Use embeddings to design active learning workflows that prioritize labeling and reduce the annotation burden for time-sensitive mapping tasks

Publish findings in top-tier journals and present at conferences

Oversee the technical direction of a dedicated postdoc and collaborate with Planet’s research scientists to transition prototypes into operational products

How You'll Work.

Team & Collaboration

Collaborate with a multi-disciplinary team of 'Planeteers' across space operations, data pipelines, and analytics; Collaborate with Planet’s research scientists

Communication Scope

Publish findings in top-tier journals; present at conferences

Process & Methodology

Oversee the technical direction of a dedicated postdoc

Full Job Description

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 world wide and joining us from offices in San Francisco, Washington DC, Germany, Austria, Slovenia, and The Netherlands. 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

Free ATS check

Applying for this Visiting Staff Scientist role?

Most applicants get filtered before a human reads their resume. See if yours makes the cut.

How to Apply on Greenhouse

  • Create a Greenhouse profile before applying — it saves time across multiple applications.
  • Upload your resume as a PDF; the parser handles it better than Word.
  • Answer all knockout questions carefully — wrong answers auto-reject before a human sees you.
  • Enable email notifications to track application status in real time.

ANONYMOUS · UNFILTERED

What do employees actually say about Planet?

Real rants from real employees. Read before you apply.

Read Company Rants →