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To enforce VITO’s remote sensing unit, we’re looking for a scientific data engineer to build services and thematic applications. Together with the team you will support remote sensing projects that are executed on openEO, which is an open-source cloud-based service for the processing of huge satellite imagery datasets. You will collaborate with data scientists and researchers that are experts in their fields. This position gives you the opportunity to work on projects with global visibility, focused on supporting the green transition towards a sustainable planet. Your work is used by the European Commission and the European Space Agency, who rely on it to provide timely and accurate information to experts working in the field, trying to have local impact while ensuring global food security or fighting climate change.
You'll become part of a talented, dedicated team working in a fast-paced, challenging international environment. A strong technical background in Python programming and data engineering in general is required to support these projects. Knowledge of earth observation or computer vision applications is a plus, but fast learners that are interested in exploring this domain are more than welcome to apply.
Most application-oriented projects use a form of machine learning to extract information from satellite or drone imagery. In this role, you continuously interact with internal and external teams that look for efficient ways to train their models and want to run them in production.
You implement techniques such as ML Ops to make these projects run smoothly and efficiently. A keen eye for constant improvement is a must to be successful in your role.
The Remote Sensing unit of VITO, as part of the larger Environmental Intelligence unit, processes petabytes of earth observation data. We primarily specialize in Big Data analysis with the use of machine learning and deep learning techniques in the application workflows. That is our passion: the extraction of ready-to-use information from the vast amounts of incoming images. Our extensive group of clients can be found within the domains of land use, biodiversity, agriculture, forestry, water management, and civil infrastructure.
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