Computer Vision Engineer

Exodigo is the leading underground mapping solution for non-intrusive discovery. Our platforms combine multi-sensor fusion, 3D imaging, and AI technologies to create complete, accurate underground maps that enable confident decision-making for customers across the built world. We transform the project lifecycle for our customers, who include key community stakeholders in the utilities, transportation and government sectors.

Our Algorithms group is a highly multidisciplinary group at the core of our data processing and detection capabilities, integrating physics, signal processing, computer vision, classical algorithms, and AI models to meet our unique requirements. Within this group, the Computer Vision Team analyzes above-ground environments from visual and multi-sensor data, and its outputs feed directly into the accuracy and completeness of the maps we deliver.

Job description

As a Computer Vision Engineer at Exodigo, you will work on problems where imagery meets the physical world. Our systems observe real above-ground environments and have to produce results that are accurate in real-world coordinates — which means the work lives in the transition between 2D imagery and 3D space: reconstruction, localization, depth, registration, and geometric reasoning about what the sensors actually saw.

The core of the role is solid computer vision engineering. Detection, segmentation, tracking, and the unglamorous work of making these tasks accurate and robust on messy real-world data are the backbone of what we build. Our stack is modern and constantly evolving — we adopt new methods as the field produces them, and we care more about whether something works on our data than about how new it is. The loop here is short — what you build reaches our mapping experts and makes an impact!

Key Responsibilities

• Own the development of vision algorithms end to end — from framing the problem using real data, through model design and iteration, to results that meet our accuracy requirements in production.
• Develop computer vision algorithms that turn imagery and multi-sensor data into a reliable interpretation of real environments — the scene understanding that our mapping outputs depend on.
• Work on the 2D-to-3D problem: geometric reasoning, reconstruction, localization, depth, and registration of visual data to real-world coordinates.
• Rapidly prototype, benchmark, and refine models against our own data and accuracy requirements.
• Work closely with our Mapping and Engineering experts to validate , and with the Software team to turn prototypes into .