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Planet

Intern, Edge Compute

Posted 13 Days Ago
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In-Office
San Francisco, CA, USA
40-60 Annually
Internship
Easy Apply
In-Office
San Francisco, CA, USA
40-60 Annually
Internship
As an AI/ML Intern, you will design computer vision models for satellites, optimize them for edge deployment, and work on improving algorithm performance in resource-constrained environments.
The summary above was generated by AI

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:

Planet's mission is to image the entire world every day, making global change visible, accessible, and actionable. We've successfully captured daily imagery of the Earth, and now we're taking the next bold step: making our spacecraft smarter and more efficient using AI and machine learning.

We are seeking a talented AI/ML Intern with an emphasis on geospatial analytics and remote sensing to join our Edge Compute team.  This is a high-impact role for an ambitious undergraduate or graduate student to work at the intersection of orbital mechanics, computer vision, and hardware-constrained systems. You will help build the algorithms of our next-generation satellites, moving beyond simple image capture to autonomous vision systems that can detect events and react to dynamic Earth conditions in real-time. The ideal candidate is passionate about AI/ML, autonomy, and squeezing performance out of neural networks to run them in the harsh, resource-constrained environment of space.

This is a full-time, hybrid role which will require you to be in our San Francisco, HQ 3 days per week.

Impact You'll Own:

  • Design and train computer vision models (object detection, segmentation, change detection) specifically optimized for satellite imagery and edge deployment.
  • Experiment with model compression techniques—including quantization, pruning, and knowledge distillation—to ensure high-performance inference on low-power hardware.
  • Explore algorithms that allow satellites to autonomously identify high-value targets (e.g., ships, wildfires, or cloud-free regions) to optimize tasking and downlink.
  • Profile and validate model performance (latency, power consumption, memory footprint) on edge hardware targets like NVIDIA Jetson or similar accelerators.
  • Assist in the curation and augmentation of "space-ready" datasets, accounting for unique orbital challenges like varying off-nadir angles and atmospheric noise.
  • Build end-to-end prototypes that demonstrate autonomous "closed-loop" systems where ML outputs directly influence satellite actions.
  • Partner with flight software engineers to transition research prototypes into robust, production-ready code for orbital environments.
  • Analyze model performance and limitations in resource-constrained environments to propose iterative architectural improvements.

What You Bring:

  • Currently pursuing or recently completed a degree in Computer Science, Robotics, Computer Engineering, Aerospace Engineering, Electrical Engineering, or a related field.
  • A solid understanding of deep learning fundamentals, particularly in Computer Vision (CNNs or Vision Transformers).
  • Proficiency in Python and hands-on experience with at least one major ML framework (e.g., PyTorch, JAX).
  • The ability to break down complex problems and a strong desire to learn how to deploy models on resource-constrained hardware.
  • Excellent communication skills with the ability to document technical workflows and explain model trade-offs (e.g., accuracy vs. speed vs power).
  • A collaborative mindset and the ability to work effectively within a cross-functional team of engineers.

What Makes You Stand Out: 

  • Hands-on experience with NVIDIA Jetson devices.
  • Previous experience with satellite imagery, GIS tools, or remote sensing data.

Application Deadline:

April 4, 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, based upon applicable law or company policy.

  • Commuter Benefits
  • Paid time off for holidays and company-wide days off
  • Internet reimbursement
  • Access to LinkedIn Learning

Compensation:

The US hourly rate range for this position at the commencement of employment is $35 - $60. The final salary range is determined by job related experience, skills and location.  The range displays our typical hiring range for new hire salaries in US locations only.  Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

San Francisco Salary Range
$40$60 USD

San Francisco Fair Chance Ordinance
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Why we care so much about Belonging. 
We’re dedicated to helping the whole Planet, and to do that we must strive to represent all of it within each of our offices and on all of our teams. That’s why Planet is guided by an ultimate north star of Belonging—dreaming big as we approach our ongoing work.  If this job intrigues you, but you’re thinking you might not have all the qualifications, please... do apply!  At Planet, we are looking for well-rounded people from around the world who can contribute to more ways than just what is listed in this job description.  We don’t just fill positions, we aspire to fulfill people’s careers, most excited about folks who are motivated by our underlying humanitarian efforts.  We are a few orbits around the sun before we get to where we want to be, so we hope you’re excited to come along for the ride. 

EEO statement:
Planet is committed to building a community where everyone belongs and we invite people from all backgrounds to apply. Planet is an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. Know Your Rights.

Accommodations: 
Planet is an inclusive community and we know that everyone has their own needs. If you have a disability or special need that requires accommodation during the hiring process, please reach out to [email protected] or contact your recruiter with your request. Your message will be confidential and we will be happy to assist you.

Privacy Policy: By clicking "Apply Now" at the top of this job posting, I acknowledge that I have read the Planet Data Privacy Notice for California Staff Members and Applicants, and hereby consent to the collection, processing, use, and storage of my personal information as described therein.

Privacy Policy (European Applicants): By clicking "Apply Now" at the top of this job posting, I acknowledge that I have read the Candidate Privacy Notice GDPR Planet Labs Europe, and hereby consent to the collection, processing, use, and storage of my personal information as described therein.

AI in Our Interviewing Process: Planet is committed to providing an exceptional interview experience for all candidates. We are currently exploring AI interviewing technologies to better focus on candidates and less on trying to capture notes. As such, with the candidate's consent, select interviews may be recorded and include a Planet AI Notetaker for transcription and summarization purposes. Should an interview involve use of AI interview technologies, the candidate will receive notification and have the ability to opt out both in advance and/or real-time. Opting out will not affect one's candidacy.

Candidate AI Policy: Planet embraces Artificial Intelligence (AI) tools, and we encourage its responsible use. We understand that candidates may use various resources, including AI tools, to prepare for interviews and assessments. However, during any live interview stage or when actively completing assessments for this position, the use of AI tools—e.g. Large Language Models (LLMs), deep fake technology, etc.—is strictly prohibited unless explicitly prompted by an interviewer or assessment instructions. If you are unsure about acceptable use, please contact your recruiter for clarification. If an AI tool or similar technology is desired as an accommodation, please contact [email protected] with your request for assistance. Your message will be confidential, and we will be happy to assist you. Violation of this policy may result in disqualification of your application.

Top Skills

Jax
Python
PyTorch

Planet San Francisco, California, USA Office

Located in sunny SOMA, just a few blocks from the San Francisco Giants ballpark. Steps from world-class restaurants and public transportation.

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