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KoBold Metals is transforming mineral exploration through AI and advanced sensor technology. The mining industry faces a critical challenge: discovering new ore deposits now requires 10X more capital than 30 years ago, while demand for copper, lithium, and other battery metals accelerates. KoBold combines proprietary AI models, novel sensor systems, and world-class geoscience expertise to guide exploration programs and make high-quality discoveries more efficiently.
As a Staff Applied Scientist, you will lead the development of next-generation instruments and data systems that power KoBold's exploration strategy. Your work spans hardware design, sensor characterization, and advanced modeling—bridging physics, statistics, and machine learning to solve complex geoscientific problems.
Key responsibilities include:
**Technical Execution:**
- Design, develop, and deploy mineral exploration data collection instruments and methods
- Develop KoBold's proprietary software exploration tools and integrate multi-source geoscientific data (geospectral, geophysical, geochemical, geologic)
- Build statistical and physics-based models to predict ore-grade mineralization locations in 2D and 3D
- Implement advanced data processing techniques—computer vision, geophysical inversions, spatially-aware clustering, anomaly detection
- Create effective visualizations for model evaluation and stakeholder communication
- Collaborate with data scientists, geoscientists, and engineers to invent algorithms combining large, complex datasets
- Work with vendors and operations teams to deploy hardware in the field
- Quantify uncertainty in data and predictions to guide iterative exploration programs
**Impact:**
You'll join an early-stage, high-impact team at a company that has already proven its approach with a world-class copper discovery and a portfolio of 60+ projects. KoBold is backed by leading institutional investors (T. Rowe Price, CPP Investments), venture capitalists (Andreessen Horowitz, Breakthrough Energy Ventures), and strategic partners (Equinor, BHP, Mitsubishi).
Required qualifications include demonstrated ability to absorb complex information with high intellectual rigor, exceptional curiosity and proactive learning mindset, and a track record of developing complex equipment with cross-disciplinary teams and vendors. Extensive technical experience in relevant areas is expected.
