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Planet logo

Intern, AI ML

Planet
Location not specified
Internship
Posted April 1, 2026
$35 - $60/hr
Not Specified
Apply Now

Application opens on company website

Job Description

The internship involves designing, prototyping, and testing edge compute modules and algorithms for processing satellite data onboard spacecraft, collaborating with machine learning teams to develop and improve onboard data analysis solutions for Planet's next-generation satellites.

Key Responsibilities

  • Design, prototype, and test edge compute modules and algorithms for onboard satellite data processing
  • Develop hardware-software co-development solutions for edge computing in spacecraft
  • Pre-process raw imagery onboard satellites to prepare data for machine learning algorithms
  • Collaborate with machine learning teams to implement deep-learning classification systems on satellite imagery
  • Explore and develop methods to improve detection performance and inference runtime in edge computing environments

Requirements

  • Experience with computer vision, machine learning, and deep learning-based approaches.
  • Ability deploying algorithms and solutions to solve real-world problems in computationally constrained environments.
  • Proficiency in C++, Python, or related tools and system software architecture.
  • MS or PhD in Electrical Engineering, Computer Science, Physics, or a related field.
  • Experience managing and doing GPU-based computing on large data sets (preferred but not explicitly mandatory).
  • Experience with machine learning on earth observation data sets (preferred but not explicitly mandatory).
  • Access to export-controlled information and the ability to do so without additional export licensing being required by the Bureau of Industry and Security and/or the Directorate of Defense Trade Controls.

Benefits & Perks

Compensation: US hourly rate range of 35 - 60 USD, final salary determined by experience, skills, and location
Work schedule: Full-time, 12-week summer internships, with specific program dates
Work environment perks: Remote work, internet reimbursement, access to LinkedIn Learning, commuter benefits, paid time off for holidays and company-wide days off
Additional benefits: Access to LinkedIn Learning, commuter benefits, paid time off for holidays and company-wide days off, internet reimbursement

Ready to Apply?

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