Remote Sensing ML Scientist for Climate AI

Remote Sensing ML Scientist for Climate AI

Full-Time 80000 - 98000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Transform satellite and radar data into actionable insights for climate solutions.
  • Company: Join Treefera, a forward-thinking company dedicated to climate AI.
  • Benefits: Enjoy remote work flexibility, competitive pay, and opportunities for growth.
  • Other info: Collaborate with a global team in a dynamic and impactful role.
  • Why this job: Make a real difference in climate action while working with cutting-edge technology.
  • Qualifications: Experience in machine learning and a passion for environmental science.

The predicted salary is between 80000 - 98000 £ per year.

Treefera seeks a Machine Learning Scientist for remote sensing to transform satellite, radar and Li DAR signals into precise intelligence.

You will develop models for plantation mapping, biomass estimation and forest monitoring with end-to-end lifecycle ownership.

You’ll work with a global team, using Python ML stack (Py Torch, scikit-learn) and geospatial tools to deliver scalable, auditable results for real-world decision-making. #J-18808-Ljbffr

Remote Sensing ML Scientist for Climate AI employer: TryApplyNow

Condé Nast is an exceptional employer, offering a vibrant work culture that fosters creativity and collaboration in the heart of Adelphi, Maryland. As a part of a globally renowned media company, employees benefit from opportunities for professional growth, access to iconic brands, and the chance to contribute to high-quality content that reaches millions. With a commitment to diversity and inclusion, Condé Nast provides a supportive environment where budding journalists can thrive and develop their skills in a fast-paced, dynamic setting.

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Contact Details:

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We think you need these skills to ace Remote Sensing ML Scientist for Climate AI

Machine Learning
Remote Sensing
Satellite Data Analysis
Radar Signal Processing
LiDAR Signal Processing
Model Development
Plantation Mapping