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Machine Learning Data Engineer Jobs in Texas (NOW HIRING)

Chevron

Lead Machine Learning Engineer

Houston, TX · On-site

$97K - $128K/yr

Chevron is seeking a Machine Learning Engineer to build and scale production AI solutions that ... In this role, you will partner with data scientists, software engineers, and domain experts to ...

Chevron

Lead Machine Learning Engineer

Houston, TX · On-site

$97K - $128K/yr

Chevron is seeking a Machine Learning Engineer to build and scale production AI solutions that ... In this role, you will partner with data scientists, software engineers, and domain experts to ...

Shipwell

Machine Learning Engineer

Austin, TX · On-site +1

Working closely with engineering, analytics, data science, and product teams, you'll take our machine learning capabilities to the next level. This is a dynamic opportunity to become the expert on ...

HCLTech

Machine Learning Engineer

Plano, TX · On-site

HCLTech is looking for an experienced AI/ML Engineer / Data Scientist to design, develop, and deploy advanced machine learning and data science solutions. The ideal candidate will have expertise in ...

Topgolf

Data Engineer II

Dallas, TX

$105K - $126K/yr

We are seeking a Data Engineer II to design, build, and maintain scalable data pipelines and data ... Prepare and deliver datasets for machine learning models for Forecasting usecases. * Implement CI ...

X4 Engineering

Machine Learning Engineer

Austin, TX · On-site

$140K - $180K/yr

This is not a pure data science role. We're looking for an engineer who enjoys building robust ... Machine Learning Engineering ✔ MLOps Engineering ✔ Platform Engineering ✔ Software ...

TalentPros.AI

Staff Machine Learning Engineer

Austin, TX

$120K - $550K/yr

We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll ... Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they ...

Abode TechZone, LLC

GCP Data Engineer

Irving, TX · On-site

$106K - $127K/yr

... machine learning data pipelines. • GCP Professional Data Engineer Certification is highly preferred. Company : Abode TechZone LLC is fast growing staffing corporation, business growth depends on ...

SWBC

Junior Data Engineer

San Antonio, TX · On-site

$103K - $124K/yr

... datasets, machine learning, and a focus on cloud-based data warehouses such as Snowflake or ... As a Junior Data Engineer, you'll gain hands-on experience building and maintaining data solutions ...

Swbc

Junior Data Engineer

San Antonio, TX · On-site

$103K - $124K/yr

... datasets, machine learning, and a focus on cloud-based data warehouses such as Snowflake or ... As a Junior Data Engineer, you'll gain hands-on experience building and maintaining data solutions ...

SWBC

Junior Data Engineer

San Antonio, TX · On-site

$103K - $124K/yr

... datasets, machine learning, and a focus on cloud-based data warehouses such as Snowflake or ... As a Junior Data Engineer, you'll gain hands-on experience building and maintaining data solutions ...

SWBC

Junior Data Engineer

San Antonio, TX

$103K - $124K/yr

... datasets, machine learning, and a focus on cloud-based data warehouses such as Snowflake or ... As a Junior Data Engineer, you'll gain hands-on experience building and maintaining data solutions ...

Cymertek

Machine Learning Engineer

San Antonio, TX · On-site

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

Futran Tech Solutions Pvt. Ltd.

Big Data Developer

Austin, TX · On-site

$52.50 - $68.25/hr

Big Data Developer Austin, TX (Day 1 onsite) - Full-time Primary Skillset: Spark, Scala, AWS ... Experience with machine learning algorithms and automated machine learning to automate and build ...

Habitat Energy

Data Engineer

Austin, TX · On-site

$113K - $136K/yr

Support best coding practices within Habitat's software, machine-learning, and data science teams. * Enhance data engineering knowledge: * Improve expertise within the software team and ensure their ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for ... engineers, and robotics experts to integrate machine learning solutions into real-world autonomous ...

Habitat Energy

Data Engineer

Austin, TX · Hybrid

$113K - $136K/yr

Support best coding practices within Habitat's software, machine-learning, and data science teams. * Enhance data engineering knowledge: * Improve expertise within the software team and ensure their ...

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All JobsMachine Learning Data Engineer JobsMachine Learning Data Engineer Jobs in Texas

Machine Learning Data Engineer information

See Texas salary details

$41.5K

$120.9K

$165.4K

How much do machine learning data engineer jobs pay per year?

As of Jul 10, 2026, the average yearly pay for machine learning data engineer in Texas is $120,851.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,700.00 and $128,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Data Engineer position, and why are they important?

To thrive as a Machine Learning Data Engineer, you typically need strong programming skills in Python or Scala, a deep understanding of data structures, algorithms, and machine learning concepts, as well as a degree in computer science or a related field. Experience with big data tools like Spark, Hadoop, and cloud platforms such as AWS or Azure, along with knowledge of data pipelines and ETL processes, is highly valuable; certifications in these areas can be advantageous. Problem-solving ability, attention to detail, and strong communication skills help professionals excel when working with diverse technical teams and stakeholders. These skills ensure data engineers can effectively build reliable, scalable data systems that support the development and deployment of machine learning models.

Can a data engineer become a machine learning engineer?

A data engineer can transition to a machine learning engineer role by gaining knowledge of machine learning algorithms, model development, and deployment techniques. Skills in programming languages like Python, experience with frameworks such as TensorFlow or PyTorch, and understanding of data pipelines are essential for this progression.

What is a Machine Learning Data Engineer job?

A Machine Learning Data Engineer is responsible for designing, building, and maintaining the data infrastructure that supports machine learning models. They develop data pipelines, ensure data quality, and optimize data storage for efficient processing. This role involves working with large-scale datasets, implementing ETL processes, and collaborating with data scientists to deploy machine learning models. Strong knowledge of databases, cloud platforms, and programming languages like Python and SQL is essential. Their work enables organizations to leverage machine learning effectively by providing reliable and scalable data solutions.

Will MLE be replaced by AI?

Machine Learning Data Engineers (MLEs) design, build, and maintain data pipelines and models that AI systems rely on. While AI automation tools can handle some tasks, MLE skills in data engineering, programming, and system architecture remain essential for developing and managing AI infrastructure effectively. The role is expected to evolve with advancements in AI, but it is unlikely to be fully replaced in the near future.

What are the typical daily responsibilities of a Machine Learning Data Engineer?

As a Machine Learning Data Engineer, your daily responsibilities often include designing, building, and maintaining data pipelines that efficiently move and transform data for machine learning applications. You may clean, preprocess, and validate large datasets, optimize storage solutions, and work closely with data scientists to ensure data is accessible and usable for model training and evaluation. Regular collaboration with software engineers and business analysts is common to align project goals and solve data-related challenges. Staying up to date with the latest tools and technologies is also important, as you'll help enable scalable and efficient deployment of machine learning solutions.

What engineers make $500,000?

Senior machine learning data engineers with extensive experience, advanced skills in data architecture, and proficiency in tools like Spark and cloud platforms can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership responsibilities, and industry reputation.

What is a $900000 AI job?

A $900,000 AI-related job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data modeling, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, strategic planning, and may require multiple years of specialized experience or advanced degrees. Compensation at this level reflects the value of expertise in developing and deploying complex AI systems in competitive industries.
What are popular job titles related to Machine Learning Data Engineer jobs in Texas? For Machine Learning Data Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Machine Learning Data Engineer jobs in Texas look for? The top searched job categories for Machine Learning Data Engineer jobs in Texas are:
Machine Learning Data Engineer jobs near you
Lead Machine Learning Engineer

Lead Machine Learning Engineer

Chevron

Houston, TX • On-site

$97K - $128K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Chevron rating

6.0

Company rating: 6.0 out of 10

Based on 214 frontline employees who took The Breakroom Quiz

56th of 74 rated oil and gas companies

Job description

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).
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 emplymnt@chevron.com.
Chevron participates in E-Verify in certain locations as required by law.

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About Chevron

Sourced by ZipRecruiter

Chevron is one of the world's leading integrated energy companies. We believe affordable, reliable and ever-cleaner energy is essential to achieving a more prosperous and sustainable world. Chevron produces crude oil and natural gas; manufactures transportation fuels, lubricants, petrochemicals and additives; and develops technologies that enhance our business and the industry. We are focused on lowering the carbon intensity in our operations and seeking to grow lower carbon businesses along with our traditional business lines. More information about Chevron is available at www.chevron.com.

Industry

Oil and coal products manufacturing, civic and social organizations and oil and gas extraction

Company size

10,000+ Employees

Headquarters location

San Ramon, CA, US

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