Geologic Modeling Machine Learning Expert

Responsibilities - Apply machine learning techniques to geologic modeling tasks including seismic interpretation, facies classification, subsurface property prediction, and geophysical inversion - Build and evaluate ML models trained on well log, seismic, remote sensing, and geochemical datasets - Develop generative and predictive models for subsurface uncertainty quantification, stratigraphic forward modeling, and basin analysis - Integrate ML approaches with physics-based geologic simulators and geostatistical workflows - Document methodologies, experimental results, and technical approaches clearly and reproducibly

Required qualifications - Published researcher with at least one first-author publication in a peer-reviewed venue (e.g., NeurIPS, ICML, Geophysics, Journal of Geophysical Research, Basin Research, or equivalent) - Master's or PhD in Geoscience, Geophysics, Geology, Earth Science, Computer Science, or a related quantitative field - Demonstrated expertise in both machine learning and geologic or geophysical modeling - Strong problem-solving skills and ability to work independently on technical and research tasks

Preferred qualifications - Hands-on experience with geoscience tools and datasets (e.g., Petrel, OpendTect, SEGY seismic data, well log databases, or similar) - Familiarity with ML applications in geoscience (e.g., seismic facies classification, well log prediction, generative geological modeling, or geophysical inversion networks) - Experience with geostatistical methods, uncertainty quantification, or physics-informed neural networks applied to subsurface systems - Background in TA'ing or teaching geoscience, geophysics, or machine learning courses

Why apply - Flexible Time Commitment – Work on your schedule while tackling meaningful scientific challenges - Startup Exposure – Work directly with an early-stage Y Combinator-backed company, gaining hands-on experience that sets you apart - Exceptional Pay – Project-based pay ranges from $150–$200/hour - Portfolio Building – Gain experience applying ML to frontier geologic modeling and earth science problems - Professional Growth – Sharpen your skills on varied, challenging subsurface and geophysical datasets and models

Employment type: Contract Time commitment: 10 hours/week Location: Remote