How to apply for Senior Software Engineer, Decision Science

About KoBold Metals

KoBold Metals uses AI to find critical minerals like copper, lithium, and cobalt. The company's first discovery, Mingomba in Zambia, was found for less than the industry average. This is a chance to work on mineral exploration as a repeatable science, not a series of guesses.

About the role

You will build software and data systems that support decision science for mineral exploration. Your work will help test subsurface predictions and improve how KoBold decides where to explore. The role is remote and full-time, and it directly supports the company's goal of finding more minerals with less spending.

A typical day

A typical day may involve writing code to improve data pipelines, meeting with data scientists and geologists to refine prediction models, and reviewing how software tools are used in exploration decisions. The exact routine is not described in the job details, so ask about team structure and daily workflows during the interview.

Who KoBold Metals is looking for

• Has senior-level software engineering experience, likely with Python or similar languages, and can design and maintain data systems.
• Has worked with decision science, probabilistic models, or prediction systems, and can turn messy data into tools that support real decisions.
• Can collaborate with data scientists, engineers, and geologists, and is comfortable working on problems where the data is incomplete or uncertain.
• Is interested in mineral exploration, electrification, or climate change, and wants to apply software skills to a physical-world problem.

Tips for this application

• In your resume, highlight projects where you built systems for prediction, decision support, or data-heavy workflows. KoBold cares about testing subsurface predictions, so show you have worked with uncertain data.
• Mention any experience with geoscience, mining, or physical-world data, even if it is not the main part of your background. It shows you understand the domain.
• Explain how your software work improved a decision, not just how it was built. KoBold wants engineers who think about outcomes.
• If you have worked remotely, say so. This role is remote, and KoBold needs people who can operate independently across time zones.
• Read about the Mingomba discovery and refer to it in your application. It shows you paid attention to KoBold's actual work, not just the job title.

What to cover in your cover letter

Focus on your experience building software for decision science or prediction systems. Explain why mineral exploration and electrification matter to you. Describe a time you worked with incomplete data and still delivered a useful tool. Show that you can work with data scientists, engineers, and geologists as a team.

Research before applying

• Read KoBold's public materials about the Mingomba discovery in Zambia, including how much was spent compared to industry averages.
• Look up the types of critical minerals KoBold targets: copper, lithium, and cobalt, and why they matter for electrification.
• Find out what KoBold says about its data systems, sensor design, and workflows for subsurface prediction.
• Check if KoBold has published anything about its tech stack or decision science methods, and note what is not public so you can ask about it.

Likely interview topics

Based on the job description, expect questions about:

• How you would design a system to test subsurface predictions when the data is sparse and expensive to collect.
• A time you worked on a decision-support tool and how you measured whether it actually helped.
• How you handle collaboration between software engineers, data scientists, and domain experts like geologists.
• Your experience with probabilistic models, Bayesian methods, or uncertainty quantification.
• Why you want to work at KoBold and how you think about the link between AI and mineral exploration.

Common mistakes to avoid

• Do not treat this as a generic software engineering role. KoBold is not a standard tech company, and the work is tied to mineral exploration and physical data.
• Do not claim to know the team, culture, or daily routine if it is not in the job details. Ask specific questions instead of guessing.
• Do not ignore the domain. If you show no interest in mining, geology, or electrification, you will look like you did not read the job description.