Note: The job is a remote job and is open to candidates in USA. KoBold Metals is a leading independent mineral exploration company focused on using AI models for mineral discovery. The Senior Software Engineer in Scientific Computing will apply software engineering and machine learning to enhance mineral exploration efforts, collaborating with data scientists and geologists to solve complex scientific challenges.
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
Skills
- 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)
- 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
Company Overview