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Machine Learning Developer Jobs in Texas (NOW HIRING)

Addison Group

Machine Learning Developer

Dallas, TX · On-site

$115K - $140K/yr

Machine Learning Developer Location (city, state): Dallas, Texas - onstie 5x a week Assignment Type: Direct Hire Pay: $115,000-$140,000 annually, plus a short-term incentive and long-term incentive.

Addison Group

Machine Learning Developer

Dallas, TX · On-site

$115K - $140K/yr

Machine Learning Developer Location (city, state): Dallas, Texas - onstie 5x a week Assignment Type: Direct Hire Pay: $115,000-$140,000 annually, plus a short-term incentive and long-term incentive.

Diamondback E&P LLC

Machine Learning Developer

Dallas, TX · On-site

$150 - $200/hr

The Machine Learning (ML) Developer is the first dedicated ML Development role in the department and is responsible for establishing the development practices, standards, and platform foundations ...

1872 Consulting

Machine Learning Engineer

Austin, TX · On-site

Degree in Computer Science, Machine Learning, or Related disciplines; and 2+ years of relevant experience -Excellence in Python -Deep expertise in algorithms and data structures -Exposure to DevOps ...

1872 Consulting

Machine Learning Engineer

Austin, TX · On-site

Degree in Computer Science, Machine Learning, or Related disciplines; and 2+ years of relevant experience -Excellence in Python -Deep expertise in algorithms and data structures -Exposure to DevOps ...

7-Eleven

Machine Learning Engineer II

Irving, TX · On-site

Hands-on experience with Azure Databricks, Azure Data Factory (ADF), Azure Kubernetes Service (AKS), Git, and Azure DevOps. * Experience building, training, validating, and deploying machine learning ...

7-Eleven

Machine Learning Engineer II

Irving, TX · On-site

Hands-on experience with Azure Databricks, Azure Data Factory (ADF), Azure Kubernetes Service (AKS), Git, and Azure DevOps. * Experience building, training, validating, and deploying machine learning ...

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Machine Learning Developer information

See Texas salary details

$17

$35

$48

How much do machine learning developer jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for machine learning developer in Texas is $35.79, according to ZipRecruiter salary data. Most workers in this role earn between $17.69 and $48.37 per hour, depending on experience, location, and employer.

What does a machine learning developer do?

A Machine Learning Developer designs, builds, and implements machine learning models and systems that enable computers to learn from data without explicit programming. They work with large datasets, select appropriate algorithms, and optimize models for various tasks such as predictions, classifications, and recommendations. Their responsibilities often include data preprocessing, feature engineering, model evaluation, and deploying models into production environments. Machine Learning Developers typically collaborate with data scientists, software engineers, and business teams to deliver AI-powered solutions.

What are the key skills and qualifications needed to thrive as a machine learning developer?

To excel as a Machine Learning Developer, you need a strong background in mathematics, statistics, programming (especially Python), and a relevant degree in computer science or related fields. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), version control systems, and cloud platforms is typically required, as are certifications in data science or AI. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data findings into actionable solutions. These skills and qualities are essential to develop accurate models, collaborate with stakeholders, and drive innovation in a rapidly evolving field.

What are some common challenges faced by machine learning developers when deploying models to production environments?

Machine Learning Developers often encounter challenges such as ensuring model scalability, managing data drift, and integrating models with existing systems during deployment. Another frequent hurdle is monitoring model performance in real time and retraining models as new data becomes available. Collaborating closely with data engineers, DevOps, and software developers is essential to streamline the deployment pipeline and maintain model reliability in production.

What is the difference between Machine Learning Developer vs Data Scientist?

AspectMachine Learning DeveloperData Scientist
CredentialsBachelor's or Master's in CS, ML, or related fields; certifications like TensorFlow or AWS MLBachelor's or Master's in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentDevelops and deploys ML models in software or cloud environmentsAnalyzes data, builds models, and provides insights for decision-making
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsUsed across industries for data analysis, predictive modeling, and insights

Both roles require strong programming skills and knowledge of ML algorithms. Machine Learning Developers focus on building and deploying models in production environments, while Data Scientists analyze data to inform business decisions. The roles often overlap but differ mainly in their primary focus and end goals.

Is machine learning a high paying job?

Machine learning developers typically earn high salaries due to the specialized skills required, such as programming in Python or R and understanding algorithms. Salaries vary based on experience, location, and industry, but overall, the role is considered well-compensated within the tech field.

What are the most commonly searched types of Machine Learning Developer jobs in Texas?

The most popular types of Machine Learning Developer jobs in Texas are:

What are popular job titles related to Machine Learning Developer jobs in Texas?

For Machine Learning Developer jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Machine Learning Developer jobs in Texas look for?

The top searched job categories for Machine Learning Developer jobs in Texas are:

Machine Learning Developer jobs near you
Infographic showing various Machine Learning Developer job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $74,449 per year, or $35.8 per hour.

Machine Learning Developer

Addison Group

Dallas, TX • On-site

$115K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 11 days ago

Job description

Job Title: Machine Learning Developer
Location (city, state): Dallas, Texas - onstie 5x a week
Assignment Type: Direct Hire
Pay: $115,000-$140,000 annually, plus a short-term incentive and long-term incentive.
Benefits: This position is eligible for medical, dental, vision, and 401(k). The company offers fully paid family benefits, a generous 401(k) match, and a competitive paid-time-off program.
Our client is a well-established energy organization with significant operations in the Permian Basin. The company is expanding its artificial intelligence and machine learning capabilities and offers a collaborative environment where employees are trusted to take ownership, contribute ideas, and influence technical direction.
We are seeking a Machine Learning Developer to serve as the first dedicated ML engineering professional within a newly established AI/ML function. This individual will create the MLOps framework, development standards, and platform foundation needed to move machine learning models from experimentation into secure, reliable production environments.
This is a hands-on individual contributor role with significant influence over the organization's future machine learning strategy. The successful candidate will be comfortable setting technical direction, recommending new approaches, and performing the detailed engineering work required to implement those recommendations. This opportunity is ideal for someone who enjoys building programs from the ground up and working in a fast-moving, entrepreneurial environment.
Key Responsibilities:
  • Develop the organization's MLOps strategy, technical standards, reusable workflows, and preferred process for moving models into production.
  • Build and support machine learning solutions within the Databricks environment.
  • Collaborate with data scientists to deploy models using tools such as MLflow, AutoML, Unity Catalog, and Databricks Model Serving.
  • Create automated CI/CD processes for model training, deployment, testing, and promotion between environments.
  • Manage the full model lifecycle, including experiment tracking, model registration, version control, lineage, governance, and user access.
  • Implement monitoring and validation processes for production models, features, and source data.
  • Establish operational visibility for ML systems and assist with troubleshooting and production support when issues arise.
  • Develop standards for data quality, feature reliability, schema validation, and data version management.
  • Produce technical documentation, reference designs, reusable templates, and engineering playbooks.
  • Lead code reviews and share best practices with data science and engineering professionals.
  • Work with business leaders, data scientists, data engineers, and IT teams to define requirements and encourage adoption of shared ML frameworks.
  • Research emerging technologies and recommend enhancements to machine learning delivery, including GenAI, agent-based systems, and AI-assisted development tools.
  • Present technical recommendations to stakeholders and confidently explain or defend a position when viewpoints differ.

Qualifications:
  • Bachelor's degree in computer science, data science, engineering, mathematics, statistics, or a related discipline is required.
  • Three to five years of experience developing, deploying, or supporting machine learning or data-intensive production systems is preferred; candidates with more advanced experience are also encouraged to apply.
  • Hands-on experience with Databricks MLflow and AutoML is required.
  • Advanced Python skills with the ability to create clean, tested, and maintainable production code.
  • Strong SQL capabilities and familiarity with Spark or another distributed data-processing technology.
  • Experience implementing or supporting MLOps practices such as automated pipelines, model deployment, production monitoring, and lifecycle governance.
  • Knowledge of software development fundamentals, including Git, unit testing, CI/CD, and common application design principles.
  • Understanding of widely used machine learning algorithms, model-training methods, evaluation techniques, and hyperparameter tuning.
  • Ability to translate complex technical topics for both technical and nontechnical audiences.
  • Strong analytical, organizational, interpersonal, and problem-solving skills.
  • Ability to work independently, manage competing priorities, and operate with limited supervision.

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