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Artificial Intelligence Machine Learning Engineer Jobs in Fort Worth, TX

7-Eleven

Machine Learning Engineer II

Irving, TX · On-site

Machine Learning Engineer II Apply Now ( Save Job Job ID R26_5112 Address 3200 Hackberry Road ... Artificial Neural Networks (ANN) and deep learning concepts. * Model evaluation, feature ...

7-Eleven

Machine Learning Engineer II

Irving, TX · On-site

Machine Learning Engineer II Apply Now ( Save Job Job ID R26_5112 Address 3200 Hackberry Road ... Artificial Neural Networks (ANN) and deep learning concepts. * Model evaluation, feature ...

7-ELEVEN

Machine Learning Engineer II

Irving, TX · On-site

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and ... Artificial Neural Networks (ANN) and deep learning concepts. * Model evaluation, feature ...

7-ELEVEN

Machine Learning Engineer II

Irving, TX · On-site

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and ... Artificial Neural Networks (ANN) and deep learning concepts. * Model evaluation, feature ...

SuperMom's LLC

Machine Learning Engineer II

Irving, TX · On-site

$150 - $200/hr

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and ... Artificial Neural Networks (ANN) and deep learning concepts. * Model evaluation, feature ...

7-Eleven

Machine Learning Engineer II

Irving, TX · On-site

As a Machine Learning Engineer II at 7-Eleven, you will collaborate with cross-functional teams and ... Artificial Neural Networks (ANN) and deep learning concepts. * Model evaluation, feature ...

Epsilon

Artificial Intelligence Engineer

Irving, TX · On-site

$73K - $136K/yr

Design, develop, and deploy machine learning and AI models that are reliable, scalable, and ... MS degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (or ...

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Artificial Intelligence Machine Learning Engineer information

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$30.2K

$123.3K

$185.3K

How much do artificial intelligence machine learning engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for artificial intelligence machine learning engineer in Fort Worth, TX is $123,291.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $148,400.00 per year, depending on experience, location, and employer.

What is an artificial intelligence machine learning engineer?

An Artificial Intelligence (AI) Machine Learning Engineer is a professional who designs, builds, and implements machine learning models and AI systems. They work with large datasets, develop algorithms, and use programming languages like Python or R to enable computers to learn from data and make predictions or decisions. Their work is essential in fields such as natural language processing, computer vision, and robotics. These engineers collaborate with data scientists, software developers, and business stakeholders to deploy AI solutions in real-world applications.

What are some common challenges faced by artificial intelligence machine learning engineers when deploying models to production?

One of the main challenges AI/ML engineers encounter is ensuring that models trained in a controlled environment perform reliably in real-world production settings. This often involves handling issues like data drift, scaling models to handle large volumes of requests, and integrating with existing infrastructure. Collaboration with data engineers and software developers is crucial to streamline deployment, monitor model performance, and address any unexpected behavior quickly. Keeping up with evolving tools and best practices is also important for long-term model maintenance and success.

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning engineer, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Engineer, you need strong programming skills (typically in Python or R), a background in mathematics or statistics, and a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn), cloud platforms, and relevant certifications are highly valuable. Problem-solving ability, creativity, and effective communication are important soft skills that distinguish top performers in this role. These competencies are crucial for designing robust AI solutions, collaborating with cross-functional teams, and driving innovation in rapidly evolving technological environments.

What is the difference between Artificial Intelligence Machine Learning Engineer vs Data Scientist?

AspectArtificial Intelligence Machine Learning EngineerData Scientist
Required CredentialsBachelor's or higher in CS, AI, ML, or related; certifications like TensorFlow, AWSBachelor's or higher in CS, Statistics, or related; certifications in data analysis or visualization
Work EnvironmentDevelops AI/ML models, coding, deploying algorithms in software environmentsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, consulting firms

While both roles involve working with data and algorithms, Artificial Intelligence Machine Learning Engineers focus on designing, building, and deploying AI/ML models in software systems. Data Scientists primarily analyze data to extract insights and support decision-making. The roles often overlap but differ in their core focus and daily tasks.

What are popular job titles related to Artificial Intelligence Machine Learning Engineer jobs in Fort Worth, TX?

For Artificial Intelligence Machine Learning Engineer jobs in Fort Worth, TX, the most frequently searched job titles are:

What job categories do people searching Artificial Intelligence Machine Learning Engineer jobs in Fort Worth, TX look for?

The top searched job categories for Artificial Intelligence Machine Learning Engineer jobs in Fort Worth, TX are:

What cities near Fort Worth, TX are hiring for Artificial Intelligence Machine Learning Engineer jobs?

Cities near Fort Worth, TX with the most Artificial Intelligence Machine Learning Engineer job openings:

Artificial Intelligence Machine Learning Engineer jobs near you
Infographic showing various Artificial Intelligence Machine Learning Engineer job openings in Fort Worth, TX as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 22% Part Time, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $123,291 per year, or $59.3 per hour.

Executive Director - Applied Artificial Intelligence Machine Learning

JPMorgan Chase & Co.

Plano, TX • On-site

$250/hr

Other

Re-posted 29 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

77th of 175 rated banks

Job description

As an Applied AI/ML Executive Director within our dynamic team, you will apply your quantitative, data science, and analytical skills to complex problems. As a Machine Learning Director, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly collaborative environment, working together with our business, technologists and control partners to deploy solutions into production. If you have a strong passion for machine learning and enjoy investing time towards learning, researching and experimenting with new innovations in the field, this role is for you.

Job responsibilities
  • Develop advanced agentic AI solutions involving structured and unstructed data, casual analytics, machine learning, deep learning, reinforcement learning, and optimization.
  • Design robust agent architectures combining LLM reasoning with tools, structured data, and APIs spanning state, memory, and context management, plus loop engineering (plan/act/observe, verification, termination, and fallback/escalation).
  • Engineer reliable agent-driven workflows emphasizing correctness, traceability, and control-aware behavior (guardrails, approvals, auditable decision paths).
  • Build knowledge-centric reasoning layers, including knowledge graphs and hybrid retrieval (RAG + graph + structured sources) to improve grounding and accuracy.
  • Drive specification-driven development: author specs and contracts (schemas, validators, tool/skill interfaces) and build evaluation/regression harnesses.
  • Advance agent quality via recursive self-improvement through automated evaluation and critique loops, red-team feedback, skill/prompt instruction optimization, and outcome-driven dataset curation (human-in-the-loop as needed).
  • Coach and mentor AI/ML team members, setting a high bar for engineering rigor and research depth.
Required qualifications, capabilities, and skills
  • PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or with at least 5 years of industry experience or an MS with at least 7 years of industry or research experience in the field.
  • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
  • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
  • Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
  • Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments

  • Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems

Preferred qualifications, capabilities , and skills:
  • Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development
  • Knowledge in search/ranking, Reinforcement Learning or Meta Learning
  • Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment and ability to develop and debug production-quality code
  • Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal
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