Intern Deep Learning Engineer - Geospatial
Offer summary
Qualifications:
Final-year Bachelor's or Master's student in Computer Science, Artificial Intelligence, Data Science, or a related field., Proficient in Python and experienced with deep learning frameworks like PyTorch, TensorFlow, or Jax., Strong understanding of the mathematics behind deep learning, including linear algebra and calculus., Demonstrated ability to take ownership of tasks and solve complex problems. .Key responsibilities:
- Collaborate with founders and tech leaders to develop impactful deep learning models.
- Work with satellite data to create solutions for monitoring soil health indicators.
- Build and refine machine learning models using various tools and frameworks.
- Deploy and scale models on Google Cloud Platform to achieve real-world impact.
Job description
🌍 Deep Learning Engineer Intern - Geospatial Data 🌍
🚀 Join us on a mission to heal the planet, one pixel at a time! 🚀
Location: 🌎 Remote with 3 hours overlap with Amsterdam time
Pay: 💶 €800/month for a minimum of 32 hours per week
Duration: 🕒 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! 🌱✨
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, we’re on a mission to empower farmers, NGOs, and corporations to regenerate soils and nurture our planet. 💪🌍
What You’ll Be Doing
💡 Get hands-on: Collaborate with founders and tech leaders to develop deep learning models that impacts our earth.
🛰️ 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.
🤖 ML magic: Build and refine machine learning models using Python, GeoPandas, PyTorch, PyTorch Geometric and TorchGeo.
☁️ Cloud diving: Deploy and scale models on GCP to create real-world impact.
🎓 Learn and grow: Supercharge your skills with our Acceleration Program, designed to make you a geospatial ML superstar! 🌟
Who You Are
- A final-year Bachelor’s or Master’s 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 (https://missing.csail.mit.edu/). 🛠️
- Experience with Google Earth Engine, Landsat, or Sentinel data. 🛰️
- Familiarity with Git and cloud platforms like GCP. 🌩️
Why Join Us?
🌟 Make an impact: Build technology that empowers farmers, NGOs, and corporations to cultivate healthier soils and drive sustainable change.
👩🔬 Work with the best: Collaborate with an all-star team of founders and leaders from top institutions and industries.
💪 Boost your career: Join our Acceleration Program to level up as a geospatial machine learning pro.
⏳ Fast-track hiring: Project review ➡️ 30-min interview ➡️ 1-week paid work trial = 🚀 start making a difference!
Required profile
Experience
Other Skills
- Collaboration
- Adaptability
- Problem Solving