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Artificial Intelligence And Machine Learning Jobs in Irving, TX

Epsilon

Artificial Intelligence Engineer

Irving, TX

$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 ...

Aivra Health LLC

AI/ML Engineer

Dallas, TX · On-site

OPT, H-1B, , or other valid US work authorization Job Summary We are seeking a motivated AI/ML Engineer to design, develop, train, and deploy machine learning and artificial intelligence solutions.

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How much do artificial intelligence and machine learning jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for artificial intelligence and machine learning in Irving, TX is $25.30, according to ZipRecruiter salary data. Most workers in this role earn between $20.53 and $26.78 per hour, depending on experience, location, and employer.

What is artificial intelligence and machine learning?

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks typically requiring human intelligence, such as reasoning, problem-solving, and understanding language. Machine Learning (ML) is a subset of AI that focuses on creating algorithms and statistical models that enable computers to learn from data and improve their performance over time without being explicitly programmed. Together, AI and ML are used in a wide range of applications, from virtual assistants and recommendation systems to autonomous vehicles and medical diagnosis. These technologies are rapidly evolving and have a significant impact across many industries.

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

To thrive as an AI/ML Engineer, you need strong skills in mathematics, statistics, programming (Python, R), and a solid understanding of machine learning algorithms, typically supported by a degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and tools like scikit-learn, as well as experience with cloud platforms and relevant certifications, is highly valuable. Critical thinking, creativity, and effective communication help in solving complex problems and collaborating across interdisciplinary teams. These skills are crucial for developing robust AI solutions that drive innovation and deliver tangible business value.

What are some common challenges faced by professionals working in artificial intelligence and machine learning roles?

Professionals in AI and Machine Learning often encounter challenges such as managing large datasets, ensuring data quality, and selecting the most appropriate algorithms for specific problems. Additionally, they must stay up-to-date with rapidly evolving technologies and frameworks, which requires continuous learning. Collaborating with cross-functional teams, such as data engineers and domain experts, is vital for translating business needs into effective AI solutions. Balancing project deadlines with the experimentation and iteration needed for model development can also be demanding.

Is artificial intelligence and machine learning a good career?

Artificial Intelligence and Machine Learning are rapidly growing fields with high demand for skilled professionals, offering competitive salaries and diverse opportunities across industries. Success typically requires strong programming skills, knowledge of algorithms, and experience with tools like Python and TensorFlow. It is considered a promising career path for those interested in technology and data analysis.

What jobs can I get with artificial intelligence and machine learning?

Jobs in artificial intelligence and machine learning include roles such as AI engineer, machine learning engineer, data scientist, research scientist, and AI software developer. These positions typically require skills in programming languages like Python or R, knowledge of algorithms, and experience with tools like TensorFlow or PyTorch. They are found across industries including technology, healthcare, finance, and automotive sectors.

What are popular job titles related to Artificial Intelligence And Machine Learning jobs in Irving, TX?

For Artificial Intelligence And Machine Learning jobs in Irving, TX, the most frequently searched job titles are:

What job categories do people searching Artificial Intelligence And Machine Learning jobs in Irving, TX look for?

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What cities near Irving, TX are hiring for Artificial Intelligence And Machine Learning jobs?

Cities near Irving, TX with the most Artificial Intelligence And Machine Learning job openings:

Artificial Intelligence And Machine Learning jobs near you
Infographic showing various Artificial Intelligence And Machine Learning job openings in Irving, TX as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $52,625 per year, or $25.3 per hour.

Executive Director - Applied Artificial Intelligence Machine Learning

JPMorgan Chase & Co.

Plano, TX • On-site

$250 - $360/hr

Other

Re-posted 26 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 174 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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