Machine Learning Engineer in LUXEMBOURG

The Client:

EVONA is partnered with an innovative company specializing in advanced satellite technology. This organization is dedicated to precise monitoring of Earth's water resources, leveraging cutting-edge satellite systems to deliver data essential for addressing global water-related challenges and supporting sustainable management practices.

In this role, you will:

• Develop and implement machine learning models to process and analyze large-scale geospatial and environmental datasets from satellite imagery, enhancing the precision of water resource monitoring.
• Work closely with cross-functional teams to understand data needs, identify challenges, and deliver actionable insights to improve water management strategies.
• Apply state-of-the-art techniques in computer vision, deep learning, and time-series analysis to extract meaningful patterns and trends from satellite data.
• Design and test scalable ML models, optimizing them for production environments, with a focus on efficiency and accuracy.
• Contribute to improving ML frameworks, tooling, and workflows to support long-term scientific research and operational goals.
• Stay updated with the latest research in machine learning and satellite data processing, proactively integrating new methodologies and advancements into ongoing projects.

To be successful, you will need:

• 3+ years of experience in machine learning or data science
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, and Scikit-Learn, along with experience in handling large datasets and cloud-based data processing.
• Ideally experience with satellite imagery and environmental data sources, plus knowledge of data preprocessing, feature extraction, and geospatial data techniques.
• Strong analytical and problem-solving skills, with an ability to work both independently and collaboratively within a team.
• An advanced degree (Master's or Ph.D.) in machine learning, data science, computer science, or a related field is preferred.

Benefits include relocation allowance and stock options!

Please apply to learn more!