Senior Software Engineer, Scientific Computing (Hardware/Sensors) at KoBold Metals

Job description

Senior Software Engineer, Scientific Computing About the Company In the coming decades, demand for critical minerals such as copper, lithium, and cobalt will continue to grow. These minerals are needed to build electric infrastructure, vehicles, data centers, and electronics. However, the mining industry is making 10x fewer discoveries per dollar spent on exploration compared to 30 years ago because the easy-to-find, near surface deposits have largely been discovered. KoBold was founded to be the first AI native mineral exploration, mine development, and technology development company. Our goal is to turn mineral exploration into a repeatable science to discover the minerals the world needs—by integrating artificial intelligence, human intelligence, and new technology. Our multidisciplinary teams of data scientists, engineers, and geologists work together to build data systems, design new sensors, and establish industry-leading workflows to develop and test subsurface predictions on our exploration projects. Our first discovery, Mingomba, is a high-grade copper deposit in Zambia, found after spending materially less than industry average. We are developing Mingomba with the same technical rigor that we apply to exploration. The Mingomba team brings together mine and processing engineers, geologists, data scientists, software engineers, and community, health & safety, construction, and operations specialists. By combining industry knowledge and cutting edge technology, we are developing Mingomba into a world class project that has safer and more predictable outcomes for ourselves, partners, and communities. It is expected to create thousands of good jobs for generations. KoBold runs exploration programs in eight countries, all with the potential for another 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 strategic natural resources companies 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. Integrate third-party and domain-specific tooling — code you did not build and cannot modify — into a coherent, repeatable pipeline: getting a heterogeneous stack to exchange data and behave correctly. 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. Debug across boundaries — third-party binaries, undocumented formats, other people's code, and deployed instrumentation — rather than escalating at the edge of your own module. 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 great candidates will have closer to 10. Work experience across many distinct technical problem types. 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. Experience with data that comes from the physical world: physical measurements, scientific instrument output, imagery, or geophysical data. Experience in 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 our data scientists in both experimental and production workflows. Capacity to dive deep on novel challenging problems in applying new technologies 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). Work practices and motivation: Ability to take ownership and responsibility of large projects. Intellectual curiosity and eagerness to learn about all aspects of mineral exploration, particularly in the geology domain. Open to working directly with geologists in the field. Enjoys constantly learning such that you are driving insights and innovations. Ability to explain technical problems to and collaborate on solutions with domain experts who aren’t software developers. A strong communicator who enjoys working with colleagues across the company. Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities. Keen not just to build cool technology, but to figure out what technical product to build to best achieve the business objectives of the company. Ability to independently prioritize multiple tasks effectively. KoBold Metals is an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity for people of any race, color, ancestry, religion, sex, gender identity, sexual orientation, marital status, national origin, age, citizenship, disability, or veteran status. This position is Full-time The US base salary range for this full-time exempt position is $170,000 - $215,000 Location: Remote, Candidates can be located anywhere in the United States or Canada. All candidates must be legally authorized to work in the United States or Canada. Compensation ranges are listed in USD. If you are based outside the US, the range may not translate directly: US pay reflects a different market with different competitive dynamics, so we benchmark roles against the local market rather than converting the listed figure.

Requirements

Must-haves

Senior Software Engineer, Scientific Computing
Architect, implement, and maintain foundational scientific computing libraries that will be used in KoBold’s mineral exploration analyses.
Integrate third-party and domain-specific tooling — code you did not build and cannot modify — into a coherent, repeatable pipeline: getting a heterogeneous stack to exchange data and behave correctly.
Debug across boundaries — third-party binaries, undocumented formats, other people's code, and deployed instrumentation — rather than escalating at the edge of your own module.
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.
At least 5 years of experience as a software engineer, data scientist or ML engineer, though most great candidates will have closer to 10.
Work experience across many distinct technical problem types.
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.
Experience with data that comes from the physical world: physical measurements, scientific instrument output, imagery, or geophysical data.
Experience in 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 our data scientists in both experimental and production workflows.
Collaborative attitude to work with stakeholders with different backgrounds (data scientists, geoscientists, software engineers, operations).
Ability to take ownership and responsibility of large projects.
Ability to explain technical problems to and collaborate on solutions with domain experts who aren’t software developers. A strong communicator who enjoys working with colleagues across the company.
Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities.
Keen not just to build cool technology, but to figure out what technical product to build to best achieve the business objectives of the company.
Ability to independently prioritize multiple tasks effectively.
This position is Full-time
Location: Remote, Candidates can be located anywhere in the United States or Canada. All candidates must be legally authorized to work in the United States or Canada.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlpython

Platform: greenhouse
Effort: quick