Geologist - Geological Data & Feature Development

Job summary

Gather, assess, clean, and standardize geological and spatial datasets while preserving their geological meaning, provenance, resolution, and uncertainty. Develop and document reusable geological representations and prototypes with the machine-learning team, and test whether they support scientifically defensible mineral exploration applications.

Job details

Geologist - Geological Data & Feature Development About 4Point AI 4Point AI develops AI for mineral exploration and subsurface understanding. We seek a geologist experienced in creating geological features or structured inputs for machine-learning models. Role Overview Build on our existing work to connect raw observations, standardized data, geological interpretation, and machine-readable inputs in a reusable framework. Develop representations that preserve spatial, sequential, relational, multiscale, and contextual information. What you will do Find, gather, and assess project and external data: drillholes, assays, maps, geophysics, remote sensing, raster layers, public datasets, and technical reports. Clean and standardize data, retaining geological meaning, source, resolution, and uncertainty. Translate interpreted alteration patterns, structural settings, host-rock relationships, and mineral-system concepts into new measurable representations. Develop prototypes or implementation specifications with our ML team; document requirements, assumptions, methods, and examples, and test their usefulness. Examples of geological representations Drillhole sequences: preserve the order of lithology, alteration, mineralization, assays, and structural observations along a hole. Spatial neighbourhoods and 3D voxels: retain local context and integrate geology, geochemistry, and geophysics for spatial prediction. Relational and multiscale features: describe proximity, direction, connectivity, stratigraphic position, and structural associations at multiple spatial scales. Contextual geological embeddings: collaborate on representations of similarities and interactions among lithologies, alteration, mineralization, and geological domains. Masked observations and cross-modal features: explicitly represent missing, censored, or unavailable information; link subsurface and surface evidence while preserving source, scale, uncertainty, and prediction-time availability. What you bring Strong understanding of exploration geology and mineral systems, developed through a geology or related geoscience degree or equivalent experience. Experience developing meaningful features or structured representations from geological data for machine-learning applications, through industry, research, or substantial academic project work. Experience interpreting geological or spatial data using GIS, geological modeling software, Python, R, or comparable tools. The ability to explain geological reasoning, question assumptions constructively, and deliver a usable prototype or precise specification. AI & technical experience These representations can support convolutional, sequence, attention, transformer, and graph models, and future foundation-model research. Advanced ML development is optional; our ML team handles architecture and training. How we work We value original ideas that can be tested and clearly documented. Experienced geologists, early-career practitioners, and master's or PhD candidates combining geology with computing or AI are welcome. A postgraduate degree is not required. Project and longer-term arrangements are open for discussion. This role goes beyond model development. It focuses on integrating geoscience expertise with AI research to ensure that the models, data interpretations, assumptions, and conclusions are scientifically defensible and geologically meaningful. You will help shape the scientific foundation of a Spatial AI company working toward increasingly general AI systems for mineral discovery. You will have a high-impact role in a small technical team where strong ideas can directly influence the product, research direction, and company trajectory. Benefits Opportunity to work on challenging AI problems in mineral exploration High-impact role in a small technical team Research-driven environment Opportunity to shape core scientific and technical workflows Competitive compensation based on experience This is a remote position.

What you’ll do

Gather, assess, clean, and standardize geological and spatial datasets while preserving their geological meaning, provenance, resolution, and uncertainty. Develop and document reusable geological representations and prototypes with the machine-learning team, and test whether they support scientifically defensible mineral exploration applications.

Requirements

Applicants should have a strong understanding of exploration geology and mineral systems, gained through a geology or related geoscience degree or equivalent experience, and experience creating meaningful geological data features or structured representations for machine-learning applications. They should be able to interpret geological or spatial data using tools such as GIS, geological modeling software, Python, or R, and clearly explain their reasoning and deliver a prototype or precise specification.

Benefits

• Opportunity To Work On Challenging AI Problems In Mineral Exploration
• High-Impact Role In A Small Technical Team
• Research-Driven Environment
• Opportunity To Shape Core Scientific And Technical Workflows
• Competitive Compensation Based On Experience

Listed skills

• Python · Preferred
• Technical Documentation · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Exploration Geology
• Mineral Systems
• Geological Data Interpretation
• Geological Feature Engineering
• Machine Learning Representations
• GIS
• Geological Modeling
• Python
• R
• Data Cleaning And Standardization
• Spatial Data Analysis
• Geochemistry
• Geophysics
• Remote Sensing
• Technical Documentation
• Scientific Reasoning

Job areas

• Science & Research
• Data & Analytics
• Technology
• Environmental & Sustainability

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