Application Guide
How to Apply for Senior Geospatial AI/ML Engineer
at Planet
🏢 About Planet
Planet uniquely combines space technology with data analytics, operating the world's largest constellation of Earth-imaging satellites. They're mission-driven to use space technology to solve Earth's toughest challenges, offering the opportunity to work with unprecedented global satellite datasets. Their remote-first culture with global offices provides flexibility while working on cutting-edge geospatial technology.
About This Role
As a Senior Geospatial AI/ML Engineer at Planet, you'll develop next-generation geospatial intelligence capabilities using satellite imagery data. This role involves building machine learning models specifically for Earth observation data, directly contributing to solutions for environmental monitoring, humanitarian response, and commercial applications. You'll be working at the intersection of satellite technology, AI, and real-world impact.
💡 A Day in the Life
A typical day involves collaborating with data scientists and domain experts to define ML requirements for geospatial problems, developing and testing computer vision models on satellite imagery datasets, optimizing model performance for large-scale processing on cloud infrastructure, and analyzing results to ensure they meet accuracy requirements for real-world applications. You'll likely participate in cross-functional meetings to translate business needs into technical solutions while staying current with the latest geospatial AI research.
🚀 Application Tools
🎯 Who Planet Is Looking For
- Expertise in developing ML models for geospatial/remote sensing data (satellite imagery, raster data, time-series analysis)
- Strong background in computer vision techniques applied to Earth observation (object detection, segmentation, change detection in satellite imagery)
- Experience with cloud platforms (AWS, GCP, or Azure) for processing large-scale geospatial datasets
- Proven ability to translate business problems into ML solutions for environmental, commercial, or humanitarian applications
📝 Tips for Applying to Planet
Highlight specific experience with satellite imagery or remote sensing data in your resume - mention specific datasets (Sentinel, Landsat, PlanetScope) or tools (GDAL, rasterio) you've used
Include concrete examples of ML projects where you processed geospatial data, emphasizing the business/environmental impact
Demonstrate understanding of Planet's mission by referencing specific use cases from their website or blog posts in your application
Show experience with distributed computing for large-scale geospatial data processing
Mention any experience with geospatial-specific ML challenges like handling different resolutions, atmospheric corrections, or temporal analysis
✉️ What to Emphasize in Your Cover Letter
["Your specific experience with geospatial AI/ML and how it aligns with Planet's mission of using space to help life on Earth", "Examples of projects where you've processed satellite imagery or Earth observation data", "How you've scaled ML solutions for large datasets similar to Planet's satellite constellation outputs", 'Your understanding of the practical applications of geospatial AI in environmental monitoring or commercial sectors']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Explore Planet's data products (PlanetScope, SkySat, RapidEye) and understand their different resolutions and use cases
- → Review Planet's blog and case studies to understand their real-world applications in agriculture, forestry, disaster response, etc.
- → Study Planet's technical documentation and APIs to understand their data pipeline and platform capabilities
- → Research Planet's recent partnerships and initiatives to understand their strategic direction
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Applying with only generic ML experience without demonstrating specific geospatial/remote sensing expertise
- Not showing understanding of the unique challenges of satellite imagery (atmospheric interference, different sensors, temporal consistency)
- Failing to connect your experience to Planet's mission of environmental and humanitarian impact
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!