What can we learn from vast archives of satellite and drone imagery? Development Seed, with support from the Earth on AWS program at Amazon Web Services, is offering a fellowship to work on innovative projects using big Earth data to address big global challenges.
As a Development Seed / Earth on AWS Data Fellow, you will collaborate with the Development Seed team to advance the field of Earth observation data. You will apply machine learning and / or data processing to advance our understanding of how Earth data can be organized and mined for deep insights. You will develop open source software that will contribute new Earth data formats, architecture or applications.
Your work will help Development Seed partners (organizations like the World Bank, the Red Cross, the Global Resilience Partnership, and NASA) to make better decisions and deliver impactful services. This fellowship is offered in a collaboration with the Earth on AWS program. Fellows will have access to AWS computing resource and will receive support and training from AWS machine learning experts.
The Fellowship is a full-time 10 week position (with permanent potential) and will allow you to learn about the industries and communities we work in, and push our team and projects forward. Your main focus will be on one of our open-source projects that supports accessible, open earth data. However, you will also have the ability to directly contribute to projects with leading civic and government organizations and have positive real world impact.
Ideal candidates have experience with:
If this sounds like you, send your resume to email@example.com. Tell us about yourself and what you’d love to work on at Development Seed. Not sure you tick all the boxes? We encourage you to apply - we have a culture of learning, and if this job description gets you excited, we want to hear from you.
Development Seed is a group of developers and designers who create positive social impact with open tech and open knowledge, specializing in platforms that derive useful insights from complex data. We build open tools to allow organizations to benefit from powerful machine learning methods. This includes Label Maker and our Skynet suite which make it easier to create feature extraction models anywhere in the world. Read more about our work on our blog, and check out our latest post around our latest machine learning work.
Earth on AWS provides open access to dozens of massive earth data archives in machine accessible formats, including Landsat, NextRad, GDELT, and OpenStreetMap data.
This position is based in DC.