Machine Learning Expert

• Develop ML and hybrid physics-ML methods for seismic imaging, inversion, and velocity model building - including ML-assisted RTM, LSRTM, and FWI.
• Apply deep learning, generative models, neural operators, and physics-informed approaches to problems such as denoising, interpolation, image enhancement, model prediction, uncertainty estimation, and automated interpretation.
• Build workflows that handle large multidimensional seismic datasets on GPU and cloud infrastructure.
• Validate new methods against established physics-based approaches, and make an evidence-based case for where they add value and where they do not.
• Move successful prototypes into production imaging workflows, with the documentation and reproducibility that requires.
• Communicate results clearly to geophysicists, data scientists, and asset teams.

• M.S. or Ph.D. in Geophysics, Applied Mathematics, Physics, Computer Science, or a related quantitative field.
• Minimum 5 years of hands-on (post academic) FWI experience: you have personally run full-waveform inversion on real seismic data. Familiarity with FWI from coursework or literature alone is not sufficient for this role.
• Demonstrated experience applying machine learning to geophysical or other physics-based scientific problems.
• Working knowledge of seismic imaging and the numerical methods behind it: wave propagation, inverse problems, and optimization.
• Proficiency in Python and hands-on experience with PyTorch, including training, validation, and performance evaluation.
• Experience working with large scientific datasets and computational workflows.
• Sound scientific judgment: the ability to design a fair comparison, recognize a result that is too good to be true, and communicate uncertainty honestly.

Additional Desired Qualifications:

• Experience with neural operators, implicit neural representations, generative models, or physics-informed neural networks applied to wave-equation problems.
• Experience combining wave physics with ML, including differentiable modeling and inversion.
• Uncertainty quantification, surrogate modeling, or ML-assisted optimization for expensive geophysical workflows.
• GPU, HPC, or distributed computing experience; AWS in particular.
• Experience with offshore or Gulf of America seismic data.
• Effective use of AI-assisted coding tools to accelerate development and debugging of scientific workflows.
• A record of research prototypes that reached production use.

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Oxy produces, markets and transports oil and natural gas to maximize value and provide resources fundamental to life. The company leverages its global leadership in carbon management to advance lower-carbon technologies and products. Headquartered in Houston, Oxy primarily operates in the United States, Middle East and North Africa. To learn more, visit Oxy

Oxy strives to attract and retain talented employees by investing in their professional development and providing rewarding opportunities for personal growth. Our goal is to meet the highest employer standards by ensuring the health and safety of our employees, protecting the environment and positively impacting our communities where we do business.