Intern, AI/ML Engineer
Planet LabsSan Francisco, CAPosted 24 March 2026
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.
Internships at Planet:
Planet’s Summer 2026 internships are full-time, paid 12-week positions located in our San Francisco HQ Office.
Program Dates:
June 1 - August 21
June 22 - September 11
About the Role:
Join Planet's Software Engineering Team as an AI/ML Software Engineer Intern focused on geospatial analytics and computer vision! We develop advanced machine-learning methods that transform large-scale imagery and sensor data into actionable intelligence about global activity spanning diverse applications.
As an intern, under the mentorship of experienced engineers and researchers, you will help design, implement, and evaluate novel AI/ML algorithms for image understanding and translate them into scalable software capabilities. You will work across the full lifecycle of Planet’s data processing, spanning RD prototyping through productization, contributing to next-generation software tools and analytics that operate across massive geospatial datasets.
This is a full-time, hybrid role which will require you to work from our San Francisco office 3 days per week.
Impact You'll Own:
Develop novel AI/ML tools for image processing and geospatial analysis
Collaborate with researchers and engineers to help translate prototype algorithms into production-ready software
Design data processing workflows and storage approaches for managing large geospatial and embedding datasets
Build tools to visualize, analyze, and communicate complex analytics and patterns
What You Bring:
Passion for exploring state-of-the-art AI/ML applying ideas to real-world problems
Programming skills in Python (or similar scientific/ML stack)
Experience with numerical computing, data processing, and ML frameworks
Currently pursuing a BS/MS/PhD in Computer Science, Machine Learning, Engineering, Applied Math, Physics, or related field.
What Makes You Stand Out:
Ability to design and implement algorithms to solve real-world data problems
Experience building data visualizations or analytics interfaces for geospatial analytics or remote sensing
Curiosity and initiative to dive into unfamiliar technical domains and rapidly build understanding
Willingness to collaborate openly, share ideas, and learn from teammates across disciplines
Application Deadline:
April 13, 2026 at 11:59p PT
EAR/ITAR Requirements:
This position requires access to export-controlled information, and as such, employment (or hiring of a contractor) is contingent upon the candidate’s ability to access all applicable export-controlled information without additional export licensing being required by the Bureau of Industry and Security and/or the Directorate of Defense Trade Controls.
Benefits While Working at Planet:
These offerings are dependent on employment type and geographical location, ... (truncated, view full listing at source)
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