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.

We are experiencing sky-rocketing growth and closed a historically large $105M Series A round in February of 2024.

As an Algorithms Developer at Exodigo, you will collaborate with exceptional talent from various disciplines to advance our core subsurface mapping technology. This role involves utilizing a blend of FEM simulation, classical algorithms, signal processing and physics to address significant challenges in the field. You will work with hardware engineers to design and enhance our sensing platforms and work alongside mechanical, algorithm and software engineers to integrate your sensing method to production.

Key Responsibilities:

• Develop and implement advanced signal processing algorithms to analyze data from our sensors.
• Collaborate with software teams to integrate your sensing method with the platforms.
• Harness physics insights and deep knowledge of the physics of our sensing platforms and propose enhanced algorithms and FEM simulations to improve data quality.
• Design and analyze experiments with our R&D field team to quickly acquire real-world data for testing your algorithms.
• Adherence to schedules within the SCRUM sprint framework.

Requirements:

• 5+ years of experience in sensor signal processing algorithm development and FEM analysis
• Expertise in Python, including numpy, scipy, etc.
• B.Sc. in Electrical Engineering - Must
• Experience in CST \ Ansys \ Pygimli, Electromagnetic low-frequency FEM
• Strong proficiency and intuition in electromagnetic physics

Preferred Qualifications:

• M.Sc. in relevant field
• Experience in Radar design
• Experience with Spatial Data analysis