Senior Software Engineer, Decision Science

• Architect, implement, and maintain decision science libraries for mineral exploration analyses
• Build tooling to increase decision-making velocity, including rapid prototyping frameworks and scalable ML pipelines
• Apply engineering best practices and coach team members on writing robust, testable code
• Collaborate with cross-functional teams to invent modern decision science technology for mineral exploration

This role contributes to building a sustainable world by enabling systematic mineral exploration and improving the discovery rate of vital energy transition metals like lithium, copper, nickel, and cobalt, which are essential for electric vehicles, renewable energy, and data centers.

• 5+ years experience in decision science with strong software engineering focus (preferably 10 years)
• Proficiency in Python, ML concepts (statistical, traditional, deep-learning), and array-based packages like xarray and numpy
• Experience building production-quality data processing solutions, MLops, and robust ML systems
• Deep experience with measured scientific data and visualizing it for domain experts
• Collaborative attitude with stakeholders from different backgrounds (data scientists, geoscientists, engineers)

The US base salary range for this full-time exempt position is $170,000 - $215,000. The position is full-time with occasional travel to exploration sites (approximately twice per year).

KoBold builds AI models for mineral exploration and deploys those models alongside novel sensors to guide decisions on exploration programs. They have become the largest independent mineral exploration company and exploration technology developer, with a portfolio of over 60 projects with discovery potential.