Senior Software Engineer, Scientific Computing (Hardware/Sensors)
KoBold Metals · Remote
About this role
**Senior Software Engineer, Scientific Computing (Hardware/Sensors)** **About the Company** KoBold builds AI models for mineral exploration and deploys those models—alongside novel sensors—to guide decisions on KoBold-owned-and-operated exploration programs. Since 2018, KoBold has become both the largest independent mineral exploration company and the largest exploration technology developer. **About the Role** KoBold believes a modern scientific computing stack will enable systematic mineral exploration and improve the rate of mineral discovery. As a member of the scientific computing team, you’ll apply software engineering and machine learning to remote-sensing, drillhole, imaging, geophysics, and other mineral exploration data—building scalable ML systems to support high-speed, high-quality decisions. You’ll collaborate with data scientists and geologists to tackle complex scientific problems and help advance discovery of vital energy transition metals like lithium, copper, nickel, and cobalt. **Responsibilities** - Architect, implement, and maintain foundational scientific computing libraries used in KoBold’s mineral exploration analyses. - Integrate third-party and domain-specific tooling into a coherent, repeatable pipeline (heterogeneous stacks that exchange data and behave correctly). - Build tooling to increase the velocity of ML progress, including: - Rapid prototyping in Jupyter notebooks - Experimentation, evaluation, and simulation frameworks - Turning R&D into robust, scalable ML pipelines - Organizing models and outputs for repeatability and discoverability - Debug across boundaries (third-party binaries, undocumented formats, other people’s code, deployed instrumentation), not just within your own module. - Apply and coach team members on engineering best practices (robust, testable, composable code). - Collaborate with data scientists, geoscientists, and engineers to invent the modern scientific computing stack for mineral exploration. - Occasional travel to exploration sites worldwide (approximately twice per year, depending on project needs). **Qualifications (Ideal Candidate)** - At least 5 years of experience as a software engineer, data scientist, or ML engineer (many candidates closer to 10). - Experience across many distinct technical problem types. - Track record building production-quality data processing solutions or tooling that delivered business value. - Proficiency with foundational ML concepts (statistical, traditional, and deep learning approaches). - Proficiency in Python, ideally including array-based packages such as xarray and numpy. - Experience working with physical-world data (physical measurements, scientific instrument output, imagery, or geophysical data). - Experience visualizing scientific data for domain experts. - Hands-on history with hardware, flight/space, lab instrumentation, or field-deployed systems. - Drive to increase the velocity and effectiveness of data scientists in both experimental and production workflows. - Ability to dive deep on novel, challenging problems in applying new technologies to mineral exploration (including understanding geology/mineral exploration practices and working with limited, disparate, noisy data). - Collaborative mindset working with stakeholders from different backgrounds (data scientists, geoscientists, software engineers, operations). **Work Practices & Motivation** - Ability to take ownership of large projects. - Intellectual curiosit
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