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Machine Learning Trainer Jobs in Texas (NOW HIRING)

Machine Learning Developer

Dallas, TX ยท On-site

$115K - $140K/yr

Job Title: Machine Learning Developer Location (city, state): Dallas, Texas - onstie 5x a week ... Create automated CI/CD processes for model training, deployment, testing, and promotion between ...

Machine Learning Developer

Dallas, TX ยท On-site

$115K - $140K/yr

Job Title: Machine Learning Developer Location (city, state): Dallas, Texas - onstie 5x a week ... Create automated CI/CD processes for model training, deployment, testing, and promotion between ...

Machine Learning Engineer Job Category: Science Time Type: Full time Minimum Clearance Required to ... Extensive experience incorporating data from multiple sources, labeling data for training, and ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Showing results 21-40

Machine Learning Trainer information

See Texas salary details

$26.1K

$81.4K

$104.8K

How much do machine learning trainer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for machine learning trainer in Texas is $81,356.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,900.00 and $103,400.00 per year, depending on experience, location, and employer.

What is a machine learning trainer?

A Machine Learning Trainer is responsible for preparing and curating datasets, fine-tuning machine learning models, and optimizing algorithms for accuracy and efficiency. They work closely with data scientists and engineers to improve model performance and ensure high-quality training data. This role involves tasks like labeling data, selecting features, and implementing preprocessing techniques. Additionally, they may develop training methodologies and evaluate models using various metrics to enhance their effectiveness.

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

To thrive as a Machine Learning Trainer, you need a solid background in computer science, statistics, and machine learning concepts, often supported by relevant academic degrees and industry experience. Familiarity with programming languages like Python, frameworks such as TensorFlow or PyTorch, and certifications like TensorFlow Developer or AWS Machine Learning are valuable assets. Excellent communication, patience, and adaptability allow trainers to effectively convey complex concepts to diverse learners. These skills ensure effective teaching, learner engagement, and successful knowledge transfer in a rapidly evolving technological landscape.

What are the typical challenges faced by a machine learning trainer in the workplace?

Machine Learning Trainers often encounter the challenge of explaining complex algorithms and abstract mathematical concepts to learners with varying levels of expertise. Adapting course materials to suit different learning styles and staying current with the latest advancements in machine learning require continuous self-development. Trainers may also need to collaborate closely with data scientists, engineers, and curriculum developers to ensure their training aligns with real-world applications. Overcoming these challenges not only enhances teaching effectiveness but also contributes to the overall growth of both trainers and their learners.

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

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

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

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

Infographic showing various Machine Learning Trainer 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 $81,356 per year, or $39.1 per hour.

Machine Learning Developer

Dallas, TX โ€ข On-site

$115K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 17 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.