Machine Learning Expert

Occidental Petroleum Corporation; United States; Presencial; USD 140.000 - 200.000; Jornada completa

Descripción de la vacante

Occidental Petroleum Corporation seeks a Machine Learning Expert for its Subsurface Innovation Imaging Team in Houston, TX. The role focuses on developing ML and hybrid physics-ML methods for seismic imaging, inversion, and velocity-model building, including ML-assisted RTM, LSRTM, and FWI.

Applicants should have 5+ years post-PhD experience with FWI on real data, strong Python and PyTorch skills, and a track record applying ML to physics-based problems.

Formación

• MS/PhD in Geophysics, Applied Mathematics, Physics, Computer Science, or a related quantitative field.
• Minimum 5 years of hands-on post-PhD FWI experience on real seismic data.
• Fluency with ML applied to geophysical or physics-based problems.
• Strong Python and PyTorch skills; experience training/validating models.

Responsabilidades

• 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 denoise, interpolate, enhance images, predict models, quantify uncertainty, and interpret data.
• Build workflows to handle large multidimensional seismic datasets on GPU and cloud infrastructure.
• Validate new methods against physics-based approaches and assess value vs. limitations.
• Move prototypes into production imaging workflows with proper documentation and reproducibility.
• Communicate results clearly to geophysicists, data scientists, and asset teams.

Conocimientos

Python

PyTorch

Geophysics

FWI experience

GPU computing

Educación

MS/PhD in Geophysics/related field

Herramientas

AWS

HPC

GPU Cluster

Descripción del empleo

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.

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.

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.

Oxy has bold ambitions to achieve net zero and help others do the same. To get there, we'll need great minds ready to unleash big ideas, strong leaders ready to inspire and team players ready to make it happen.

Oxy produces energy and essential products to sustain and improve life on our planet. Our experienced teams, located in the United States, Middle East and Africa, are committed to safe and efficient operations and products, and to reducing our carbon footprint and helping others do the same. We are busy developing the big ideas and broad solutions we will need to achieve net zero. Every day, we get closer. And we won't stop until we're there.