Algorithm Team Lead (Geophysicist/Physicist)

Description:

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.

Exodigo is looking for a Geophysicist/Physicist to join our algorithms team. In the role, you will need to innovate and solve subsurface imaging problems using a combination of multidisciplinary domains in Geophysics, Math, and Computational Science in the Geotech domain. The role includes research tasks that require understanding of elasticity and electromagnetics domains, optimizations methods, and Python programming language. 

Responsibilities:  

• Owns technical vision and prioritization for the team 
• Mentors and unblocks team members 
• Reviews critical PRs and ensures code quality 
• Drives sprint planning and estimation 
• Takes responsibility for delivery timelines and team performance 
• Hands-on coding: 30–50% of time 

• B.Sc. in Geophysics or Physics. 
• Three years of experience in a relevant industry, working with real data. 
• Proficiency in geophysical signal processing (seismic, ground penetrating radar, ERT, FDEM) 
• Knowledge of Geotech data acquisition processes (e.g., SPT, CPT) 
• Experience with Linux-based systems and Python programming language  
• Demonstrated ability to conceive of and develop creative/innovative technology. 
• Demonstrated teamwork, strong communication skills, and collaboration in complex projects. 

Bonus points: 

• Proficiency in deep learning algorithms and frameworks.  
• Working with modern source control. 
• Proficiency in numerical modeling of elastic and EM wave propagation. 
• Proficiency in optimization methods to solve inverse problems.