Senior Software Engineer, Decision Science

October 29

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KoBold Metals

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Artificial Intelligence • Science • Energy

KoBold Metals is a company specializing in advanced mineral exploration. By investing over $100 million annually across 60+ projects on five continents, KoBold is at the forefront of using artificial intelligence and novel hardware to transform mineral exploration into a repeatable science. The company aggregates comprehensive data on the Earth's crust and utilizes proprietary AI tools, including the Machine Prospector® system, to minimize uncertainties in exploration. KoBold Metals is committed to ethical exploration practices and is backed by world-class investors dedicated to discovering and developing new battery metal resources. Their innovative approach leverages AI to build the world's largest geoscience information collection and model subsurface data statistically.

51 - 200 employees

Founded 2019

🤖 Artificial Intelligence

🔬 Science

⚡ Energy

📋 Description

• Architect, implement, and maintain decision science libraries that will be used in KoBold’s mineral exploration analyses. • Build tooling to increase the velocity of our decision making, including enabling rapid prototyping in Jupyter notebooks; build experimentation, evaluation, and simulation frameworks; turning successful R&D into robust, scalable pipelines; and organizing ML models and their outputs for repeatability and discoverability. • 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 decision science technology 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.

🎯 Requirements

• At least 5 years of experience in the field of decision science with a strong software engineering focus, though most great candidates will have closer to 10. • Track record of building production quality data processing solutions or tooling that have delivered business value • Proficiency with foundational concepts of ML, including statistical, traditional and deep-learning approaches • Proficiency in Python, ideally including array-based packages such as xarray and numpy • Deep experience with measured scientific data • Experience in visualizing scientific data for domain experts • Experience in MLops and in the making of robust ML systems • Drive to increase the velocity and effectiveness of our data scientists in both experimental and production workflows • Capacity to dive deep on novel challenging problems in applying decision science to mineral exploration, including understanding a complex domain of geology and mineral exploration practices as well as working with limited, disparate and noisy data sources • Collaborative attitude to work with stakeholders with different backgrounds (data scientists, geoscientists, software engineers, operations)