Hydrosat is a data analytics and satellite Earth observation company leveraging thermal infrared and multi-spectral data to deliver insights into crop health, drought and wildfire risk, industrial activity, and defense situational awareness to government and commercial customers. Our data analytics team in Luxembourg applies proprietary algorithms to thermal imagery and combines this with data fusion capabilities to extract valuable insights. 

We are seeking a machine learning engineer in Luxembourg to develop state of the art machine learning models in support of our commercial products. This role will appeal to candidates with a strong scientific background who are looking to use their data science and machine learning skills to make an impact on the world in agriculture, climate, and public safety monitoring applications.

What you’ll do

• Conduct original research in machine learning, deep learning, and artificial intelligence to solve complex problems.

• Design, develop, and optimize novel machine learning models and algorithms.
• Extract valuable information from satellite imagery and turn it into actionable insights for agriculture.
• Work with new and emerging technologies including Python data science tools.
• Work with high performance computing platforms.
• Integrate data sources and work with the software development team to deliver data products to customer endpoints.
• Identify and mitigate technical and schedule risks during development.

Requirements

• Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related field.
• 3+ years of machine learning development experience using multiple tools, technologies and frameworks.
• Strong analytical skills and critical mindset, with the ability to build innovative solutions.
• Strong background in statistics and probability theory.
• Proficiency in Python, with the ability to learn new languages and technologies quickly.
• Fluency in software development tools and practices (version control, test, debugging, continuous integration/continuous development).
• Highly self-motivated, keen learner able to solve challenging problems with creative solutions.
• Extensive experience processing satellite imagery (Sentinel, Landsat, VIIRS, MODIS datasets) and using geo information technology and raster data processing tools (GDAL, Rasterio, Geopandas).
• Strong team player with demonstrated ability to take ownership and drive execution.
• Demonstrated ability to effectively collaborate with internal and external teams to deliver capability to users.

Desired Qualifications

• Experience implementing land-cover classification or time-series forecasting models.
• Experience deploying machine learning models in a production environment.
• Working knowledge with AWS or other cloud provider (GCP, Azure).
• Experience with containerization.
• Experience with high performance computing platforms (HPC).

Benefits

• Competitive salary 
• Employee equity 
• Flexible and dynamic startup environment 
• Professional development opportunities 
• Access to great facilities at the Luxembourg House of Startups building