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Machine Learning Assistant Jobs in Coppell, TX (NOW HIRING)

Addison Group

Machine Learning Developer

Dallas, TX · On-site

$115K - $140K/yr

Job Title: Machine Learning Developer Location (city, state): Dallas, Texas - onstie 5x a week ... Establish operational visibility for ML systems and assist with troubleshooting and production ...

Addison Group

Machine Learning Developer

Dallas, TX · On-site

$115K - $140K/yr

Job Title: Machine Learning Developer Location (city, state): Dallas, Texas - onstie 5x a week ... Establish operational visibility for ML systems and assist with troubleshooting and production ...

CVS Health

Sr Machine Learning Engineer

Irving, TX · On-site +1

$112K - $185K/yr

Benchmark different algorithms for scalability and performance under different data and system conditions. Assist in defining the architecture of software systems involving machine learning ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... assistants. * Enforce Enterprise Guardrails: Ensure all AI/ML applications strictly adhere to ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $130K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... assistants. * Enforce Enterprise Guardrails: Ensure all AI/ML applications strictly adhere to ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... assistants. * Enforce Enterprise Guardrails: Ensure all AI/ML applications strictly adhere to ...

Crowe LLP

Machine Learning Engineer

Plano, TX · On-site

$62K - $100K/yr

Write high-quality, production-ready code and assist in code reviews to maintain standards of excellence. * Develop and implement comprehensive testing protocols, including smoke tests and unit tests ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94K - $129K/yr

... Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

Crowe LLP

Machine Learning Engineer

Dallas, TX

$62K - $100K/yr

Write high-quality, production-ready code and assist in code reviews to maintain standards of excellence. * Develop and implement comprehensive testing protocols, including smoke tests and unit tests ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX · On-site

$94K - $129K/yr

... Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

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All JobsMachine Learning JobsMachine Learning Assistant JobsMachine Learning Assistant Jobs in Coppell, TX

Machine Learning Assistant information

See Coppell, TX salary details

$12

$16

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How much do machine learning assistant jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for machine learning assistant in Coppell, TX is $16.67, according to ZipRecruiter salary data. Most workers in this role earn between $15.10 and $17.74 per hour, depending on experience, location, and employer.

What is a machine learning assistant?

A Machine Learning Assistant is a professional who supports the development, implementation, and maintenance of machine learning models and systems. They assist data scientists and engineers by preparing datasets, conducting preliminary data analysis, running experiments, and helping to optimize algorithms. This role often involves coding, testing models, and ensuring the quality and reliability of machine learning solutions. Machine Learning Assistants play a key role in streamlining workflows and enabling faster progress in AI projects.

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

To thrive as a Machine Learning Assistant, a solid background in mathematics, statistics, programming (often Python), and foundational knowledge of machine learning algorithms is essential, typically supported by a relevant degree or coursework. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems such as Git is commonly required. Strong problem-solving abilities, attention to detail, and the capability to communicate findings effectively are standout soft skills in this role. These skills ensure accurate data analysis, effective model building, and successful collaboration within multidisciplinary teams.

What are some common challenges a machine learning assistant may face when supporting data preparation and model training?

Machine Learning Assistants often encounter challenges such as cleaning large, unstructured datasets, identifying and handling missing or inconsistent data, and ensuring data privacy compliance. They also need to communicate effectively with data scientists and engineers to understand project requirements and adapt to evolving priorities. Staying organized and managing multiple tasks simultaneously—such as data preprocessing, feature engineering, and running model experiments—is crucial for success in this role.

What are the most commonly searched types of Machine Learning jobs in Coppell, TX?

The most popular types of Machine Learning jobs in Coppell, TX are:

What are popular job titles related to Machine Learning Assistant jobs in Coppell, TX?

For Machine Learning Assistant jobs in Coppell, TX, the most frequently searched job titles are:

What cities near Coppell, TX are hiring for Machine Learning Assistant jobs?

Cities near Coppell, TX with the most Machine Learning Assistant job openings:

Machine Learning Assistant jobs near you
Infographic showing various Machine Learning Assistant job openings in Coppell, TX as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 18% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $34,665 per year, or $16.7 per hour.

Machine Learning Developer

Addison Group

Dallas, TX • On-site

$115K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 8 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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