Senior Software Engineer, KoBold Metals
Scientific Computing
$170-215k
Salary applicable to US applicants only
More information about location
AI-powered mineral exploration company
Open for applications
AI-powered mineral exploration company
201-500 employees
Open for applications
$170-215k
Salary applicable to US applicants only
More information about location
201-500 employees
Company mission
To create value by discovering new ore deposits and expanding existing resources.
Role
Who you are
- At least 5 years of experience as a software engineer, data scientist or ML engineer, 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 ML 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
What the job involves
- 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
- 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
- This position is Full-time
Our take
Supported by billionaires Bill Gates, Jeff Bezos and Richard Branson, KoBold Metals utilises AI and Cloud computing techniques to assess the composition of the subsurface in order to explore metals that are used in making batteries installed in electric vehicles and clean energy technologies.
KoBold is a force in its field with significant financial backing, not just from the aforementioned tycoons, but thanks to Andreessen Horowitz, one of Silicon Valley’s leading venture capital funds. In 2019, this enabled KoBold to have funding available for four years, which, since then, has financed explorations at various locations, including Greenland.
As the climate crisis intensifies, the world has increasingly moved towards sustainability and hence demand for sustainable products like EVs has gone up, increasing the need for KoBold’s mineral exploration services. With recent approval for backing a new copper mine in Zambia, along with additional funding, the growing demand for sustainable resources positions KoBold for a promising future.
Steph
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 5 rounds)
Nov 2025
$163m
LATE VC
Jan 2025
$527m
SERIES C
Total funding: $1.1bn
Company HQ
Downtown Berkeley, Berkeley, CA
Leadership
Kurt House
(Co-Founder & CEO)Previously founded a carbon Sequestration and enhanced oil recovery venture as well as a natural gas asset acquisition platform. They also worked in Private Equity and Corporate Consulting at Bain & Company and spent time as an Adjunct Professor at Stanford University.
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