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KoBold Metals

AI-driven mineral exploration for critical metals

Staff Applied Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Demonstrated ability to quickly absorb and synthesize complex information, with a track record of high intellectual rigor in a professional setting.
  • Exceptional curiosity and eagerness to learn, with a proactive approach to exploring new concepts and technologies.
  • A successful track record of developing complex equipment with cross-disciplinary teams and vendors.
  • Extensive experience with physical measurement and data analysis systems using phenomena such as optics, electromagnetism, radiation, and gravity.
  • Experience applying scientific knowledge to identify and prototype emerging technologies.
  • Experience with systems integration and data acquisition.
  • Experience with Python data science packages and general software engineering practices.
  • Experience with collaborative software development using Git and familiarity with software engineering best practices such as unit and integration test suites and continuous integration and continuous deployment pipelines.
  • Experience with SQL and familiarity with non-relational databases.
  • Experience with cloud computing resources.
  • Experience building predictive models, applying them to different problems, and evaluating and interpreting results.
  • Experience with data analysis, physics analysis, and applied statistics across a broad range of data types, including data from physical systems.
  • Ability to investigate challenging applications of machine learning to mineral exploration, including understanding geology and mineral exploration practices and working with limited, disparate, and noisy data sources.
  • Experience deploying sensors in the field.
  • Ability to take ownership and responsibility for large projects.
  • Ability and willingness to learn about mineral exploration, particularly geology, and work directly with geologists in the field.
  • Ability to explain technical problems to domain experts who are not software developers and collaborate on solutions with colleagues across the company.
  • Comfort working in a dynamic, fast-growing early-stage company and taking on a range of responsibilities.
  • Ability to identify the technical products best suited to achieving business objectives.
  • Ability to independently prioritize multiple tasks effectively.
  • All candidates must be legally authorized to work in the United States or Canada.
  • All employees must travel to project sites at least one week per year; field-facing and technical roles spend significantly more time in the field.

Responsibilities

  • Design, develop, and deploy new mineral exploration data collection instruments and methods.
  • Help develop KoBold’s proprietary software exploration tools.
  • Find and curate geospectral, geophysical, geochemical, geologic, and geographic data and integrate it into KoBold’s proprietary data system.
  • Build models to make statistically valid predictions about the locations of compositional anomalies within the Earth’s crust.
  • Create visualizations to evaluate model performance and enable rapid interaction with underlying data and key features.
  • Develop and apply data processing, statistical, and physics-based techniques to geoscientific data, from computer vision to geophysical inversions, and use the results to guide targeting efforts and inform acquisition and exploration decisions.
  • Present to and collaborate with external partners and stakeholders.
  • Implement statistically rigorous spatially aware clustering, anomaly detection, and other analysis methods to advance analysis capabilities.
  • Collaborate with data scientists, geoscientists, and engineers to develop and deploy algorithms combining large and complex datasets for mineral exploration and discovery.
  • Simulate, characterize, and calibrate sensor performance and design new data acquisition systems.
  • Work with vendors and partners to build hardware and collaborate with operations staff to deploy it in the field.
  • Build models and apply scientific computing, statistical, and physics-based methods to identify evidence of ore-forming processes and predict ore-grade mineralization locations in two and three dimensions.
  • Help build a worldwide dataset for the exploration program, identifying and quantifying uncertainty in data and predictions.
  • Work with geoscience colleagues to identify opportunities and technologies for geophysical data collection, create two- and three-dimensional geologic predictions, identify exploration targets, design field programs, and use collected data to reduce uncertainty and guide subsequent field work.
  • Build and deploy next-generation hardware and use data tools to solve scientific problems.

Desired Qualifications

  • Experience with remote sensing.
  • Experience creating machine learning models on geospatial data.
  • Experience with image processing or computer vision.
  • Experience with project and team management.

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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