Application Guide
How to Apply for Intern, Machine Learning & AI
at Planet
🏢 About Planet
Planet uniquely combines space technology with data science, operating the world's largest constellation of Earth-imaging satellites to provide global environmental monitoring. Their mission-driven focus on solving real-world problems through satellite data makes them appealing for those wanting to apply AI/ML to meaningful environmental and humanitarian challenges.
About This Role
This Machine Learning & AI Intern will work on developing models to analyze Planet's massive satellite imagery dataset, likely focusing on environmental monitoring, object detection, or data quality improvements. The role is impactful because it directly contributes to Planet's mission of using space technology to address global challenges like climate change, deforestation, and disaster response.
💡 A Day in the Life
A typical day might involve developing and testing computer vision models on Planet's satellite imagery datasets, collaborating with data scientists and engineers to deploy models for environmental monitoring applications, and participating in team discussions about improving data quality or developing new analysis techniques for global challenges.
🚀 Application Tools
🎯 Who Planet Is Looking For
- Strong foundation in machine learning (especially computer vision, geospatial analysis, or time-series data)
- Experience with Python ML frameworks (TensorFlow, PyTorch) and geospatial libraries (GDAL, rasterio)
- Understanding of satellite imagery or remote sensing data processing
- Ability to work with large-scale datasets in cloud environments (AWS/GCP)
📝 Tips for Applying to Planet
Highlight any experience with satellite imagery, geospatial data, or remote sensing projects in your portfolio
Demonstrate understanding of Planet's specific mission by mentioning how your ML skills could address environmental monitoring challenges
Show familiarity with large-scale data processing by describing projects involving terabytes of image/video data
Include links to GitHub repositories with relevant computer vision or geospatial ML projects
Reference specific Planet datasets or applications you're excited to work with (like monitoring deforestation or urban development)
✉️ What to Emphasize in Your Cover Letter
['Your specific interest in applying ML to Earth observation and environmental challenges', 'Examples of relevant technical experience with image analysis or large datasets', "Understanding of Planet's unique position as both a space and data company", 'How your skills could contribute to specific applications like disaster response or climate monitoring']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Explore Planet's public data catalog and understand their different satellite constellations (Dove, SkySat)
- → Review Planet's applications in environmental monitoring, agriculture, or disaster response
- → Study their technical blog posts about ML/AI applications for satellite imagery
- → Understand their business model and how different sectors (commercial, government, humanitarian) use their data
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Applying with generic ML experience without showing interest in geospatial or satellite data applications
- Failing to demonstrate understanding of Planet's specific mission beyond 'working with space data'
- Not having concrete examples of working with image data or large datasets in your application
📅 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!