This is an opportunity to join one of the most ambitious software product development teams working in Earth Observation in Portugal. Our mission is to develop scalable software applications for the space downstream market with a strong focus on sustainability, infrastructure monitoring, climate, carbon, and security-related applications.
We are looking for a Remote Sensing & Geospatial AI Engineer to support the development of Earth Observation products and services based on satellite imagery, geospatial data, and artificial intelligence models. The role focuses on the development of algorithms, models, and methodologies that can be transitioned from R&D into operational and scalable software products.
The ideal candidate should have at least 3 years of relevant professional experience. Exceptional junior candidates, senior profiles and/or PhD candidates with relevant research and applied experience are also encouraged to apply.
As a member of the Space Digital R&D team, you will:
- Prototype, develop, and validate AI and remote sensing algorithms to create Earth Observation products
- Develop machine learning and deep learning models for geospatial and satellite imagery analysis
- Evaluate, select, and implement advanced statistical and modeling approaches and ensure proper model validation and generalization
- Contribute as a technical expert to the product development process
- Continuously propose improvements to geospatial and AI components of products and services
- Design and support validation campaigns, field tests, and collaborative research activities
- Work with Product Managers to define and implement the R&D roadmap aligned with product strategy
- Collaborate with software engineering teams to transition models and prototypes into scalable production systems
- Monitor and leverage state-of-the-art methods from scientific literature and commercial solutions
- Use open data, open-source tools, and proprietary data to develop new EO methodologies and applications
- Produce technical documentation and white papers describing methodologies, algorithms, and use cases
Typical application areas include:
- Land Use / Land Cover mapping and change detection
- Carbon stock and sequestration estimation
- Forestry and environmental monitoring
- Critical infrastructure monitoring
- Urban analysis
- Security and defence applications
- Very High Resolution optical and SAR data exploitation
Qualifications
Education:
- Master’s degree in Aerospace/Geospatial Engineering, Remote Sensing, Computer Science, Data Science, Physics, Engineering, or related field
- PhD in a relevant field is a plus
Professional Experience:
- Minimum 3 years of experience in remote sensing, geospatial analytics, or AI/ML applied to geospatial data
- Experience developing and deploying machine learning models
- Experience working with satellite imagery and geospatial datasets
Technical Skills:
- Strong programming skills in Python (mandatory)
- Experience with AI/ML frameworks (such as MLFlow, TensorFlow, PyTorch, Scikit-learn)
- Experience with geospatial tools and libraries (such as QGIS, GDAL, Rasterio, GeoPandas)
- Experience in image processing, computer vision, or pattern recognition
- Understanding of supervised, unsupervised, semi-supervised, and transfer learning techniques
- Experience with model validation and performance assessment
- Experience handling large geospatial datasets
Highly valued experience in one or more of the following areas:
- Land Use / Land Cover classification and change detection
- Carbon estimation and biomass modelling using remote sensing
- Forestry applications and environmental monitoring
- SAR, InSAR, or PolSAR data processing
- Object detection, segmentation, and feature extraction in satellite imagery
- Automated ground-truth generation and data labeling workflows
- Experience deploying models into production environments
Soft Skills:
- Ability to work both autonomously and in a team environment
- Strong problem-solving and analytical skills
- Proactive and innovation-driven mindset
- Good communication skills
- Fluency in English (mandatory)
Additional Information
- Relaxed work environment, dynamic and multidisciplinary teams.
- We facilitate and promote a balanced and healthy lifestyle, coordinating work with personal life.
- Health insurance.
- Partnerships with gyms and others.
- Up to three additional vacation days.
- Birthday day off.