Role overview
Spexi is a drone technology company on a mission to make ultra-high-resolution geospatial imagery more accessible than ever before, empowering humanity to make better decisions about the physical world.
We’re building an exciting new two-sided marketplace called the Spexi Network, powered by drones and blockchain technology. It's the world’s first Fly-to-Earn platform that enables drone pilots to earn rewards for flying and collecting aerial imagery. It also enables organizations of all sizes to quickly and easily access high-resolution aerial imagery and valuable derivative data, powering remote monitoring of buildings, infrastructure, natural resources, and more. Our goal is to guide their decision-making and help them better plan and react, without needing to own drones or hire pilots.
We’re looking for a Senior Applied Research Engineer to lead the development of experimental algorithms and prototype systems that push the boundaries of what’s possible with geospatial imagery. Your work will bridge early-stage research and production—delivering high-quality, well-structured code that serves as a foundation for the next generation of Spexi’s geospatial intelligence products.
What you'll work on
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Develop and prototype novel algorithms in computer vision, 3D geometry, and geospatial processing that enable automated understanding, alignment, and retrieval of aerial imagery and its derivatives.
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Design approaches to improve spatial accuracy of imagery using photogrammetric principles, including bundle adjustment and camera pose estimation, with limited or no ground control data.
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Investigate methods for geometric and semantic understanding of imagery, including feature extraction, image segmentation, and object-level matching across views.
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Work with coordinate reference systems, projection transforms and georectified imagery.
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Write performant and maintainable code in C++ and Python to support prototyping and handoff to production engineering teams.
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Design prototypes enabled by scalable pipelines for handling spatially indexed data, using tools like PostGIS and cloud-native services in AWS.
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Stay current on advances in 3D reconstruction (e.g., multi-view stereo, SLAM, radiance fields) and apply relevant techniques to aerial data workflows.
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Collaborate cross-functionally with product and engineering teams to evaluate feasibility, scope impact, and translate concepts into concrete implementation plans.