InSAR R&D Engineer (Contract)

KorrAI is looking for an InSAR Processing & R&D Engineer to work on specific high impact problems in our InSAR pipeline. This is not a generic GIS or remote sensing role. We are looking for someone who has worked close to the InSAR processing stack and understands how these systems behave in practice. You will work on focused technical scopes such as atmospheric correction, co registration, calibration, and interferogram quality. The goal is to take known gaps in our pipeline and turn them into working, production ready improvements. This role sits between research and engineering. You should be comfortable implementing methods, not just evaluating them. What this role is This is a scoped, part time contractor role focused on improving specific components of an existing InSAR pipeline. We already know the key problem areas. The work is to pick them up, solve them properly, and integrate improvements back into the system. You will not be building from scratch. You will be improving a production system where performance, accuracy, and scalability matter. These are independent, well defined technical scopes, not a single long project. Example areas of work Depending on fit and priority, scopes may include: Improving atmospheric correction methods across C band, L band, and X band data Investigating and improving co registration performance and diagnostics Enhancing interferogram quality control and error detection Improving calibration workflows using GNSS and validation sites Supporting unwrapping related R&D and quality assessment Testing and integrating methods from research into the pipeline Evaluating processing tradeoffs across sensors, DEMs, and stack configurations Contributing to scalable processing components for large area workflows What you’ll do Take ownership of a defined technical scope and propose an approach Review relevant literature and existing pipeline behavior Implement and test solutions in Python within a Linux environment Work with the team to validate outputs against real world data such as GNSS and reference sites Document results, limitations, and next steps Deliver work that can be integrated into the production pipeline What we’re looking for We are looking for someone who has worked hands on with InSAR processing and can operate close to the core pipeline. This role is focused on solving real technical problems in a production system, not just analyzing outputs. Hands on experience with InSAR processing including interferograms, co registration, atmospheric effects, unwrapping, and calibration Comfortable working close to the processing pipeline, not just GIS or visualization layers Ability to take a method or idea and implement it into a working solution Strong Python skills and comfort working in Linux environments Experience with Git and collaborative development workflows Ability to debug real world issues such as noise, coherence loss, and DEM errors Not a pure researcher or generic GIS profile. Looking for someone who can both understand the science and build systems Familiarity with SNAP, ISCE, StaMPS, Gamma, or similar tools Experience working with multiple SAR sensors such as Sentinel 1, TerraSAR X, COSMO SkyMed, or SAOCOM Experience with cloud or batch processing environments such as AWS or Docker Experience with validation approaches such as GNSS, corner reflectors, or ground truth data This role suits someone who enjoys solving technically challenging problems and can contribute quickly without heavy structure. Working style This role is best suited to someone who likes solving narrow, technically challenging problems and can work independently with minimal supervision. You should be comfortable working with partial context and figuring things out without full specifications. Engagement structure Part time contractor role up to around 20 hours per week Initial engagement of up to 6-12 months with potential extension Work is structured around specific technical scopes Remote To apply - Please send a short message covering: A brief note on your hands-on InSAR experience and the type of pipelines you have worked on Tools, frameworks, and SAR datasets you have worked with One or two concrete examples of technical problems you have solved in an InSAR pipeline and your approach Your weekly availability Your expected rate