KoBold Metals
Senior Software Engineer, Decision Science
Vaga remota de Software Engineering com fit claro de localização do candidato.
Publicada2 de jul. de 2026
Países elegíveis9 países aceitos
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Resumo da vaga
Senior Software Engineer, Decision Science
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
Responsibilities
- 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.
Our ideal candidate will have:
- 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)
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.
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