Top 35 Lead machine learning Jobs in Houston, Tx

Lead Machine Learning Engineer
Chevron —Houston, TX
- Email
- 7 years
- Computer Science
- Engineering
8d
Licensed Real Estate Agent: Leads, AI CRM & Weekly Live Training | Houston, TX
White Picket Realty —Houston, TX
- $67,920.86 - $81,797.16 a year
- Part-time
- Mid-level
- Office
- Real Estate License
- Flexible schedule
Quick Apply
Lead Product Manager - AI Developer Platform
Scribd, Inc. —Houston, TX
- $141,000 - $256,500 a year
- Full-time
- 7 years
- Residential
- AWS
- Paid parental leave
- Disability insurance
AI LEAD L1
Wipro Limited —Houston, TX
- $60,000 - $135,000 a year
- 5 years
- Pass drug screening
- System design
- Disability insurance
- Health insurance
2d
AI Tools Architect / Tech Lead
Hewlett Packard Enterprise —Spring, TX
- $160,000 - $349,000 a year
- Full-time
- Computer Science
- Bachelor of Science
- Office
Lead Data Scientist
Memorial Hermann Health System —Houston, TX
- Full-time
- 7 years
- Computer Science
- Engineering
3d
Palantir foundary lead
DUO2 LLC —Houston, TX
- $120 - $125 an hour
- Contract
- Azure
- Computer Science
- 3 years
Quick Apply
1d
Lead Data Scientist
Octave Intelligence —Houston, TX
- Remote
- Computer Science
- 5 years
- HIPAA
2d
Finance Operate - Manager, Innovation Lead
Deloitte —Houston, TX
- $128,000 - $252,500 a year
- Full-time
- 7 years
- Machine learning
- Product management
13d
AI Experience Lead
HP —Spring, TX
- $130,700 - $205,200 a year
- Full-time
- Marketing
- 8 years
- Product management
- Paid parental leave
- Paid holidays
3d
Software Engineering Service Management Lead
KBR —Houston, TX
- Full-time
- Computer science
- Computer Science
- 5 years
- AD&D insurance
- Health insurance
8d
Lead, AI Engineering
Bain & Co. —Houston, TX
- $179,500 - $203,500 a year
- Full-time
- Azure
- Office
- 3 years
- Wellness program
- Paid holidays
Quick Apply
Lead, Engineering Analytics
Saber Power Services —Houston, TX
- Full-time
- Engineering
- Mid-level
- Analysis skills
- Disability insurance
- Health insurance
Quick Apply
Google AI Lead Architect
Deloitte —Houston, TX
- $141,000 - $278,000 a year
- Full-time
- Azure
- Computer Science
- Up to 50% travel
Microsoft D365 CRM or Copilot/AI Functional Lead, Senior Associate
PRICE WATERHOUSE COOPERS —Houston, TX
- $77,000 - $202,000 a year
- Azure
- Mid-level
- 3 years
- Paid holidays
- Health insurance
Salesforce Life Science Patient Service Delivery Lead
Accenture —Houston, TX
- $122,700 - $302,400 a year
- Full-time
- 5 years
- Machine learning
- US work authorization
- Paid holidays
- Disability insurance
Business Data Scientist Sr/Lead
Williams Companies —Houston, TX
- Full-time
- Hybrid work
- Computer Science
- Office
- SQL
- Free parking
- Health savings account
Sr SAP Tech Lead (ABAP, BTP and AI)
The Friedkin Group —Houston, TX
- Full-time
- Computer Science
- Customer service
- Research
- Health insurance
- Dental insurance
RedHat Offering Lead - (Private AI, Containers, Automation)
Accenture —Houston, TX
- $122,700 - $338,300 a year
- Full-time
- Hybrid work
- 6 years
- Travel
- US work authorization
- Paid holidays
- Disability insurance
Salesforce Life Science Technology Lead
Accenture —Houston, TX
- $68,300 - $218,800 a year
- Full-time
- Mid-level
- 3 years
- Machine learning
- Paid holidays
- Disability insurance

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Lead Machine Learning Engineer

Chevron -
Houston, TX

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Job Details

Full-time
8 days ago

Qualifications

AI models
Software engineering
Continuous Delivery (CD) implementation
Engineering development testing
Enterprise software
Application deployment
AI platforms (beyond public GPTs)
Scalable systems
Production systems
Machine learning cloud services
Machine intelligence
Model deployment
Version control systems
Developing large-scale AI models
Scalability
Model training
System deployment
Technical troubleshooting support
Distributed computing
DevOps automation
Cross-functional collaboration
Model evaluation
Machine learning frameworks
Python
Master data management
MLOps
Cross-functional communication

Full Job Description

Total Number of Openings

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.

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. These systems are built on and integrated with enterprise data platforms and systems, enabling scalable, cross-domain use of AI across upstream operations. The resulting solutions are used directly by engineers and geoscientists to improve reservoir understanding, optimize production, and enhance drilling and completions performance.

This is a high-impact role focused on deploying AI at scale. You will bridge the gap between experimentation and production while delivering measurable business outcomes across Chevron’s upstream operations.

Responsibilities for this position may include but are not limited to:

Solution Design & Development

Design and deliver production-grade machine learning solutions aligned with business workflows and enterprise architecture
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

Model Operationalization

Convert prototypes into reliable, production-ready solutions deployed in distributed and cloud-native environments
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
Ensure solutions meet enterprise standards for security, reliability, and maintainability

Deployment & Integration

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
Integrate ML solutions with APIs, enterprise systems, and downstream business applications
Leverage automation to improve delivery speed, consistency, and reliability

Monitoring & Maintenance

Implement monitoring, alerting, and observability for deployed models and data pipelines
Detect and address model drift, data quality issues, and performance degradation
Partner with stakeholders to ensure model outputs drive accurate, consistent, and high-value decisions
Troubleshoot complex system and integration challenges across distributed environments

Required Qualifications:

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.
Proven track record of deploying machine learning models and enterprise data-driven platforms into production environments at scale.
Solid understanding of the AI/ML lifecycle, including data preparation, model training, evaluation, deployment, and inference.
Experience with Azure cloud services, including Azure Machine Learning, data platforms, and enterprise integration patterns.
Experience building and maintaining CI/CD pipelines and applying DevOps practices for ML systems.
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.

Preferred Qualifications:

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.
Deep understanding of model lifecycle management, performance optimization, and ML system design patterns in enterprise environments.
Experience deploying, operating, monitoring, and optimizing generative AI systems, including agent-based and AI-assisted decision-support solutions in enterprise environments.
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:

Expatriate assignments will not be considered.

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

U.S. Regulatory notice:

Chevron is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religious creed, sex (including pregnancy), sexual orientation, gender identity, gender expression, national origin or ancestry, age, mental or physical disability, medical condition, reproductive health decision-making, military or veteran status, political preference, marital status, citizenship, genetic information or other characteristics protected by applicable law.

We are committed to providing reasonable accommodations for qualified individuals with disabilities. If you need assistance or an accommodation, please email us at [email protected].

Chevron participates in E-Verify in certain locations as required by law.

Apply Now

Refine Your Search

lead machine learning jobs in houston, tx

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