Chevron

Lead Machine Learning Engineer

Houston, Texas, United States of America

No sponsorshipDetected 27 days ago

PythonDistributed SystemsAzureCI/CDDevOpsMachine LearningData EngineeringData ScienceLLMsMLOpsA/B Testing

About the role

Total Number of Openings 1 Chevron is accepting online applications for the position Machine Learning Engineer, Subsurface and Wells Insights through 07/08, 2026 at 11:59 p.m. (Central Time).
These systems are built on and integrated with enterprise data platforms and systems, enabling scalable, cross-domain use of AI across upstream operations.
This is a high-impact role focused on deploying AI at scale.

Partner with data scientists, data engineers, and IT teams to integrate models into enterprise data platforms, pipelines, and digital products
Collaborate with subsurface and wells domain experts to translate business challenges into deployable AI/ML solutions
Select appropriate data sources, technologies, and design patterns to solve complex problems using AI/ML
Support integration of ML capabilities into tools used by geoscientists, reservoir engineers, and drilling and production teams
Implement end-to-end MLOps practices, including model versioning, automated retraining, and lifecycle management
Optimize models for performance, scalability, latency, and cost efficiency
Configure infrastructure to support resilient and highly available ML workloads
Build and maintain CI/CD pipelines for automated model testing, deployment, and release
Deploy and manage models using cloud-native tooling such as Azure ML, containerization, and orchestration platforms
In this role, you will partner with data scientists, software engineers, and domain experts to transform advanced AI/ML models into reliable, enterprise-grade systems.

Bachelor's degree in Engineering, Computer Science, Data Science, or a related technical field.
Minimum 7 years of hands-on experience in software engineering, ML engineering, or enterprise data platforms
Strong proficiency in Python with solid software engineering fundamentals including testing, version control, and modular application design.
Strong understanding of data governance principles (e.g., Lineage, MDM) and integration across enterprise systems.
Demonstrated ability to troubleshoot complex distributed systems and work across cross-functional teams.

Master's or Ph.D. in Engineering, Computer Science, Data Science, or a related field.
10+ years of relevant technical and enterprise experience in AI, data platforms, or digital transformation.
Experience with large-scale enterprise data architectures and complex analytical workloads.
Domain experience in upstream oil & gas, including subsurface, wells, and production.
Experience enabling AI adoption, defining enterprise roadmaps, and delivering measurable business value through data and AI solutions.
Relocation Options:
Relocation will not be considered.
International Considerations:

Design and deliver production-grade machine learning solutions aligned with business workflows and enterprise architecture
Chevron is accepting online applications for the position Machine Learning Engineer, Subsurface and Wells Insights through 07/08, 2026 at 11:59 p.m. (Central Time).
Chevron is seeking a Machine Learning Engineer to build and scale production AI solutions that drive critical decisions across subsurface and wells operations.

We are committed to providing reasonable accommodations for qualified individuals with disabilities.

Equal Opportunity employer.
If you need assistance or an accommodation, please email us at emplymnt@chevron.com.

Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position.

This listing is sourced directly from Chevron's careers page and normalized into a canonical job model.