Research Engineer – Satellite DSM Generation Platform Part-time NEW

Research Engineer – Satellite DSM Generation Platform

We are seeking a technical Research Engineer to contribute to a Proof-of-Concept project funded by Digital Futures and hosted at KTH Geoinformatics Division.

The project builds on research showing that LiDAR-quality Digital Surface Models (DSMs) can be generated from a single optical satellite image, using deep-learning model. The goal is to take this research from prototype to an on-demand DEM/DSM platform, tested with real stakeholder.

You will be the core engineering hire for the project, working directly with the Principal Investigator and a small team of researchers to turn a validated research method (TRL 6–7) into a working platform ready for first users.

The successful candidate will:

• Design and build the on-demand DSM/DEM processing platform, from ingestion of a single optical satellite image to delivery of a high-resolution DSM output
• Integrate and deploy the existing deep-learning DSM generation model into a production-ready pipeline
• Develop the infrastructure needed to serve first pilot areas selected by priject stakeholders
• Build demo/prototype tooling to showcase platform accuracy and usability to stakeholders
• Support data quality, benchmarking against reference sources (e.g. Copernicus DSM, LiDAR DSM), and documentation
• Collect and incorporate user feedback to refine the platform toward an MVP
• Work closely with the research team at KTH Geoinformatics

Requirements:

• A graduate degree or an advanced level (higher education) in the research subject or equivalent competence.
• Documented experience in programming (e.g., Python or similar)
• Experience building or deploying data pipelines, APIs, and cloud-based systems
• Interest or background in geospatial data, remote sensing, or Earth Observation
• Ability to work independently and take ownership of engineering deliverables
• Good communication skills in English, as this will be required in day-to-day work

Preferred qualifications:

• Experience with deep learning frameworks and deploying ML models in production
• Familiarity with cloud environments and containerized applications
• Experience handling large and heterogeneous geospatial datasets (satellite imagery, DEMs/DSMs)
• Background in Photogrammetry, Computer Vision, or Geoinformatics
• Experience with ESA data and cloud infrastructure
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality

Great emphasis will be placed on personal skills.