Senior Software Engineer, Decision Science
KoBold Metals2 months ago
Base Salary
$170k - $215k/yr
Responsibilities
- Architect, implement, and maintain decision science libraries for mineral exploration analyses.
- Build tooling for rapid prototyping, experimentation, evaluation, simulation, scalable production pipelines, and repeatable ML model organization.
- Apply and coach robust, testable, and composable software engineering practices.
- Collaborate with data scientists, geoscientists, and engineers to develop decision science technology for mineral exploration.
- Travel to exploration sites approximately twice per year depending on project needs.
Requirements
- At least 5 years of decision science experience with a strong software engineering focus.
- Track record of building production-quality data processing solutions or tooling that delivered business value.
- Proficiency in foundational machine learning concepts, including statistical, traditional, and deep-learning approaches.
- Proficiency in Python, ideally including xarray and NumPy.
- Deep experience with measured scientific data and visualizing scientific data for domain experts.
- Experience with MLOps and robust machine learning systems.
- Ability to work with novel decision science problems, complex geology and mineral exploration domains, and limited, disparate, and noisy data.
- Ability to take ownership of large projects, prioritize tasks independently, communicate technical problems to non-developer domain experts, and collaborate across disciplines.
- Willingness to learn about mineral exploration and work directly with geologists in the field.
Benefits
- Full-time exempt position.
- Remote role open to candidates located anywhere in the United States or Canada.
- Employees are expected to travel to project sites, with a minimum of one week per year; field-facing and technical roles spend significantly more time in the field.
- Equal opportunity and affirmative action employer.
Tech Stack
NumPyPython
Categories
About KoBold Metals
KoBold Metals develops AI-driven mineral exploration software and sensor systems and runs its own exploration programs to find copper, lithium, and other battery metals. The privately held company, founded in 2018 and headquartered in Berkeley, California, combines data science with geoscience to guide drilling and asset decisions. It is backed by investors such as Andreessen Horowitz, Breakthrough Energy Ventures, BHP, Mitsubishi, T. Rowe Price, and CPP Investments.