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KoBold Metals

AI-driven mineral exploration for critical metals

Senior Software Engineer - Decision Science

Software EngineeringConfirmed live in the last 24 hours
Full-time$170k - $215k

About the Job

Requirements

  • At least 5 years of experience in decision science with a strong software engineering focus.
  • A track record of building production-quality data-processing solutions or tooling that delivered business value.
  • Proficiency with foundational machine-learning concepts, 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 visualizing scientific data for domain experts.
  • Experience with machine-learning operations and building robust machine-learning systems.
  • Capacity to address novel, challenging problems in applying decision science to mineral exploration, including understanding geology and mineral-exploration practices and working with limited, disparate, and noisy data sources.
  • Ability to take ownership and responsibility for large projects.
  • Ability to explain technical problems to domain experts who are not software developers and collaborate on solutions with them.
  • Ability to independently prioritize multiple tasks effectively.
  • All candidates must be legally authorized to work in the United States or Canada.

Responsibilities

  • Architect, implement, and maintain decision science libraries for mineral-exploration analyses.
  • Build tools to increase decision-making velocity, including enabling rapid prototyping in Jupyter notebooks; building experimentation, evaluation, and simulation frameworks; turning successful research and development into robust, scalable pipelines; and organizing machine-learning models and 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 develop decision-science technology for mineral exploration.
  • Travel occasionally to exploration sites worldwide to observe the impact of scientific computing on exploration products and design new technologies; travel is approximately twice per year depending on project needs, with at least one week per year expected for all employees.

Desired Qualifications

  • Experience with Python array-based packages such as xarray and NumPy.
  • Most strong candidates will have closer to 10 years of decision-science experience.

About the Company

KoBold Metals

AI-driven mineral exploration for critical metals

KoBold Metals uses artificial intelligence to accelerate the discovery of lithium, cobalt, copper, and nickel deposits for clean energy. Its main product is an AI-driven mineral exploration program that combines a proprietary EOI tool with large-scale data about the Earth’s crust to decide which data to collect at each exploration step and reduce uncertainty. It stands out from traditional explorers through heavy data gathering, a multidisciplinary team, and a data-powered, repeatable scientific process. Its goal is to locate and sell mineral deposits to clean-energy companies, speeding the supply of critical minerals for batteries and renewable energy technologies.

Company size
201-500
Company stage
Late Stage VC
Total funding
$1.1B
Headquarters
Berkeley, CA
Founded
2018

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