Intern Deep Learning Engineer - Geospatial
Spatialise
๐ Deep Learning Engineer Intern - Geospatial Data ๐
๐ Join us on a mission to heal the planet, one pixel at a time! ๐
Location: ๐ Remote with 3 hours overlap with Amsterdam time
Pay: ๐ถ โฌ800/month for a minimum of 32 hours per week
Duration: ๐ 6+ months
Who We Are
Welcome to Spatialise, where we blend geospatial magic, machine learning wizardry, and a deep commitment to sustainability to shape the future of agriculture! ๐ฑโจ
Founded by a dream team of innovators from Wageningen University, ex-IBM leadership, machine learning experts from Bain & BCG, and researchers from the University of Utrecht, weโre on a mission to empower farmers, NGOs, and corporations to regenerate soils and nurture our planet. ๐ช๐
What Youโll Be Doing
๐ก Get hands-on: Collaborate with founders and tech leaders to develop deep learning models that impacts our earth.
๐ฐ๏ธ Satellite sleuthing: Work with cutting-edge data like Sentinel1, Sentinel2 and Modis to develop next-gen solutions for monitoring soil health indicators like Soil Organic Carbon.
๐ค ML magic: Build and refine machine learning models using Python, GeoPandas, PyTorch, PyTorch Geometric and TorchGeo.
โ๏ธ Cloud diving: Deploy and scale models on GCP to create real-world impact.
๐ Learn and grow: Supercharge your skills with our Acceleration Program, designed to make you a geospatial ML superstar! ๐
Who You Are
A final-year Bachelorโs or Masterโs student in Computer Science, Artificial Intelligence, Data Science, or an equivalent field.
Passionate about solving real-world problems and eager to learn.
Skilled in Python and have experience with deep learning with Pytorch, Tensorflow, Jax, or similar.
Skilled in the mathematics behind deep learning, including linear algebra and calculus.
Demonstrated end-to-end ownership in your tasks and enjoy working on complex problems.
Enjoy converting research ideas in quick actionable output that can directly be tested for project.
Bonus points if you have
Good experience with the tools mentioned in the MIT Missing Semester of Your CS Education course. ๐ ๏ธ
Experience with Google Earth Engine, Landsat, or Sentinel data. ๐ฐ๏ธ
Familiarity with Git and cloud platforms like GCP. ๐ฉ๏ธ
Why Join Us?
๐ Make an impact: Build technology that empowers farmers, NGOs, and corporations to cultivate healthier soils and drive sustainable change.
๐ฉโ๐ฌ Work with the best: Collaborate with an all-star team of founders and leaders from top institutions and industries.
๐ช Boost your career: Join our Acceleration Program to level up as a geospatial machine learning pro.
โณ Fast-track hiring: Project review โก๏ธ 30-min interview โก๏ธ 1-week paid work trial = ๐ start making a difference!