Intern, Software Engineering, AI
Planet LabsSan Francisco, CAPosted 12 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:
The Manufacturing Software Infrastructure Team builds the tools and systems that enable our team to scale. We tackle projects large and small, from building our own in-house Manufacturing Execution System (MES) to automating deployments to our hardware testing stations. Our systems track manufacturing processes and data, spacecraft test results, telemetry, and much more. We collect tons of data and metrics, and use this to feed back into the teams for continual process improvement. As a member of the software infrastructure team, you will be responsible for building and deploying features used by spacecraft engineers and technicians, collaborating with other teams to build or use API integrations, troubleshoot complex problems, and fearlessly experiment with new methods and technologies.
For this role, we are specifically looking for an individual with considerable experience in integrating artificial intelligence models into existing tools and systems. This individual will be experimenting with a relatively new technology and blazing the trail for its integration into our production systems. To be successful in this role, the candidate should be self-directed; eager to conduct research and bring new knowledge to the team; be unafraid to experiment, iterate, and backtrack; and be able to apply their existing knowledge and experience to a new domain.
This is a full-time, in-office position based in our San Francisco office 5 days per week.
Impact You'll Own:
Research and develop AI tools to solve manufacturing systems problems
Develop and document new APIs and database schemas
Collaborate with team members
Interview users to gather feedback and requirements, then develop and present mockups for review
Implement new features on the frontend and backend, then demo these features for the team
Develop prototypes and proof of concepts
Conduct code reviews
What You Bring:
Currently enrolled in a graduate program in the field of artificial intelligence, Machine Learning and LLMs, or a related field
Experience using ML methods to classify data
Experience with MCP, skills, and other methods to enable tool use by LLMs
Experience integrating with or building REST APIs
Web development experience
Experience with relational databases
What Makes You Stand Out:
Have developed integrated applications using AI/ML technology
Application Deadline:
April 5, 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 ca ... (truncated, view full listing at source)
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