Machine Learning Engineer/Remote Sensory SME.

  • technology
  • permanent
  • Berlin

Machine Learning Engineer-Remote Sensing SME | Hybrid in Berlin| 3-4 stage process | €70-90k per annum

I am partnered with a client based in Berlin looking to expand their ML team and I am searching for a talented Machine Learning Engineer with expertise in remote sensing to join their team in Berlin (flexible Hybrid work arrangements possible). In this role, you will play a key part in developing and deploying machine learning models that extract valuable information from satellite imagery and other remote sensing data sources.


  • Design, develop, and implement machine learning models for tasks such as object detection, classification, and time series analysis of remote sensing data.
  • Pre-process and prepare remote sensing data for machine learning applications.
  • Develop and manage data pipelines for efficient data ingestion and processing.
  • Collaborate with data scientists and engineers to define project requirements and ensure successful model integration.
  • Stay up-to-date on the latest advancements in remote sensing and machine learning.
  • Communicate technical concepts effectively to both technical and non-technical audiences.


  • Master's degree in Computer Science, Engineering, Physics, or a related field.
  • Minimum 3 years of experience in machine learning with a focus on remote sensing applications.
  • Proven experience in developing and deploying machine learning models in production environments.
  • Strong programming skills in Python (familiarity with libraries like scikit-learn, TensorFlow, or PyTorch is a plus).
  • Experience with data pre-processing techniques for remote sensing data (e.g., radiometric correction, geometric correction).
  • Excellent communication and collaboration skills.


  • Competitive salary and benefits package.
  • Opportunity to work on challenging and impactful projects.
  • Collaborative and supportive work environment.
  • Flexible work arrangements (remote work possible).
  • Continuous learning and development opportunities.

Please apply with your CV, email and contact number. Or alternatively reach out to me on LinkedIn