Senior Software Engineer, Scientific Computing

Senior Software Engineer, Scientific Computing About the Company The mining industry has steadily become worse at finding new ore deposits, requiring >10X more capital to make discoveries compared to 30 years ago. The easy-to-find, near-surface deposits have largely been found, and the industry has chronically under-invested in new exploration technology, relying on the manual techniques of yesteryear – even as demand accelerates for copper, lithium, and other metals to build electric vehicles, renewable energy, and data centers. KoBold builds AI models for mineral exploration and deploys those models—alongside our novel sensors—to guide decisions on KoBold-owned-and-operated exploration programs. In the six years since founding, KoBold has become by far both the largest independent mineral exploration company and the largest exploration technology developer. Our data scientists and software engineers, who come from leading technology companies, jointly lead exploration programs with our renowned exploration geologists. KoBold has proven its first discovery with materially less capital than the industry average and found one of the best copper deposits ever discovered: the copper is far more concentrated than the global average of copper mines, and this asset alone is expected to generate meaningful revenue for decades. KoBold has a portfolio of more than 60 other projects, each of which has the potential for another high-quality discovery. KoBold is privately held; investors include institutional asset managers T. Rowe Price and Canada Pension Plan Investments; technology venture capitalists Andreessen Horowitz, Breakthrough Energy Ventures, BOND Capital, Durable Capital, StepStone, and Standard Investments; and natural resources companies Equinor, BHP, and Mitsubishi. About the Role At KoBold we believe that a modern scientific computing stack will enable systematic mineral exploration and materially improve our rate of mineral discovery. This role is a key ingredient to this strategy. As a member of our scientific computing team, you will apply software engineering and machine learning to remote-sensing, drillhole, imaging, geophysics and other mineral exploration data in order to build scalable ML systems to help make high-speed, high-quality decisions for our mineral exploration projects. Collaborating with our exceptional team of data scientists and geologists, you will tackle complex scientific problems head-on and collectively pave the way for discoveries of vital energy transition metals like lithium, copper, nickel, and cobalt. Together we can shape the future of mineral exploration and contribute to building a sustainable world. Responsibilities Architect, implement, and maintain foundational scientific computing libraries that will be used in KoBold’s mineral exploration analyses. Build tooling to increase the velocity of our machine learning progress, including enabling rapid prototyping in Jupyter notebooks; build experimentation, evaluation, and simulation frameworks; turning successful R&D into robust, scalable ML pipelines; and organizing models and their outputs for repeatability and discoverability. In collaboration with data scientists, build models to make statistically valid predictions about the locations of economic concentrations of ore metals within the Earth’s crust. Apply–and coach team members to use–engineering best practices such as writing robust, testable and composable code Collaborate with data scientists, geoscientists and engineers to invent the modern scientific computing stack for mineral exploration Occasional travel to exploration sites around the world to observe the impact of scientific computing on KoBold’s exploration products and design new technologies to further discovery. Travel is approximately twice per year depending on project needs. Qualifications Our ideal candidate will have: At least 5 years of experience as a software engineer, data scientist or ML engineer, though most