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GenAI Data Scientist, Subsurface & Well Operations

Job in Houston, Harris County, Texas, 77246, USA
Listing for: MyPetroCareer.com
Full Time position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Science Manager
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

About Exxon Mobil

At Exxon Mobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. We are one of the world’s largest publicly traded energy and chemical companies, powered by a unique and diverse workforce. The success of our Upstream, Product Solutions and Low Carbon Solutions businesses comes from the talent, curiosity and drive of our people who bring solutions to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies.

We invite you to bring your ideas to Exxon Mobil to help create sustainable solutions that improve quality of life and meet society’s evolving needs.

About Houston:
Exxon Mobil’s state-of-the-art campus north of Houston serves as home to its Upstream, Product Solutions and Low Carbon Solutions businesses. The facility opened in 2014 and accommodates more than 10,000 employees and visitors. The campus brings global functional groups together to foster collaboration, creativity and innovation and to attract, develop and retain top talent. It is located in Spring, Texas, on 385 wooded acres near I-45 and the Hardy Toll Road, about 25 miles from downtown Houston.

What

role you will play in our team
  • Work on complex AI use cases from ideation and discovery through deployment and sustainment as part of integrated, enterprise-level teams.
  • Collaborate with Exxon Mobil subject matter experts to strengthen organizational capabilities in AI/ML.
  • Support business teams in making impactful, data-driven decisions.
What You Will Do
  • Lead the scoping, design, development, and deployment of AI/ML solutions, primarily focused on Generative AI applications for subsurface and well-related operations.
  • Collaborate with data and machine learning engineers to operationalize models and ensure seamless integration with existing digital infrastructure.
  • Build and deploy AI system components (such as chatbots, agents, and other workflow automation components) capable of interacting with diverse data sources and providing insightful information to users.
  • Develop and implement solutions involving orchestration of multiple AI agents to achieve complex tasks.
  • Apply domain knowledge and physical principles to improve model accuracy and reliability.
  • Contribute to the growth of internal AI capabilities by sharing expertise and developing best practices.
  • Provide technical mentorship and guidance to colleagues across teams.
  • Work closely with team leads and subject matter experts to align on project priorities, strategy, and solution design.
  • Optimize end-to-end AI solutions to enhance performance, usability, and cost.
  • Work closely with the business to understand problems and translate them into mathematical frameworks; help enhance business adaptability for the solution.
  • Validate AI system responses, including troubleshooting prompt engineering, agentic workflows and other aspects of a GenAI system.
  • Develop processes and automation for accelerating validation of AI systems, while ensuring an appropriate degree of accuracy.
About You Skills / Qualifications
  • 5+ years of professional experience in developing and deploying AI/ML solutions, with a strong emphasis on Generative AI technologies and applying these methods to physical systems and engineering workflows.
  • Deep expertise in natural language processing (NLP), large language models (LLMs), and building agentic workflows for Generative AI with the ability to understand underlying mathematics and develop novel algorithms.
  • Solid understanding of knowledge graphs, ontologies, and semantic technologies.
  • Foundations in AI/ML on data processing, probability and statistics, EDA, feature engineering, modeling strategy, model development, and explainable AI.
  • Proven track record of developing and deploying end-to-end Generative AI solutions, notably multi-agent systems, in business environments.
  • Proficient in Python and ML frameworks such as Tensor Flow, PyTorch, and Scikit-learn.
  • Proficient in Generative AI frameworks such as Langchain, Prompt flow, or Copilot Studio.
  • Ability to uncover meaningful insights from complex datasets and to test hypotheses with rapid validation of assumptions.
  • Strong communication,…
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