Machine Learning Expert

Occidental Petroleum Corporation; Houston (TX); On-site; USD 150,000 - 230,000; Full time

Job summary

Occidental Petroleum Corporation is seeking a Machine Learning Expert for its Subsurface Innovation Imaging Team in Houston, TX. The role focuses on ML and hybrid physics-ML methods to advance seismic imaging, inversion, and velocity-model building on large GPU datasets.

You will implement deep learning, neural operators, and physics-informed models; validate against physics-based baselines and translate successful prototypes into production workflows.

Qualifications

• MS or PhD in a quantitative field relevant to geophysics.
• Minimum 5 years postdoc/industry FWI experience on real data.
• Proficient in Python and PyTorch, with ML in physics-based problems.

Responsibilities

• Develop ML and hybrid physics-ML methods for seismic imaging and inversion.
• Apply ML/physics-informed approaches to denoising, interpolation and uncertainty.
• Build GPU and cloud workflows for large seismic datasets.
• Move prototypes into production imaging workflows with documentation.

Skills

Python

PyTorch

Geophysics ML

Seismic imaging

FWI

ML for physics-based problems

Large datasets

Uncertainty quantification

Education

MS or PhD in Geophysics/Applied Math/Physics/CS

Tools

Python ecosystem

AWS / cloud

GPU/ HPC

Job description

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 OxyOxy 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.We are looking for a motivated individual to fill the position of Machine Learning Expert within our Subsurface Innovation Imaging Team based in Houston, TX .Essential Job Responsibilities: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.Qualifications: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.Occidental does not offer sponsorship of employment-based nonimmigrant visa petitions for this role.Recruitment FraudIt has come to our attention various individuals and/or organizations are contacting people falsely pretending to recruit on behalf of Oxy. Please be aware that these recruiting scams and communications do not originate nor are they associated with our recruitment process. All Oxy job postings and offers will require a completed application through our company website.Oxy does not charge a fee at any stage of the recruiting process. We will never:• Ask you to pay for applications, interviews, meetings, processing, training or for any other fees• Use recruiting or placement agencies that charge candidates an advance fee of any kind or• Request personal information such as passport and bank account details at an early stage of our recruitment process.We recommend against responding to unsolicited business propositions or offers from people you don't know. Do not disclose your personal or financial details. If you believe you have been the victim of a recruiting scam, please contact your local police department.All qualified applicants will receive consideration for employment without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.