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Artificial Intelligence Machine Learning Physics Jobs in Grapevine, TX

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.

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 ...

Artificial Intelligence * Machine Learning * Data Science * Computer Engineering * Software Engineering * Information Systems * or related technical field * Master'''''s degree from a US university ...

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Artificial Intelligence Machine Learning Physics information

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

As of Sep 12, 2026, the average hourly pay for artificial intelligence machine learning physics in Grapevine, TX is $18.54, according to ZipRecruiter salary data. Most workers in this role earn between $11.54 and $23.56 per hour, depending on experience, location, and employer.

What is artificial intelligence machine learning physics?

Artificial Intelligence Machine Learning Physics is an interdisciplinary field that applies AI and machine learning techniques to solve complex problems in physics. Experts in this area use algorithms to analyze large datasets, model physical phenomena, and accelerate scientific discoveries. The field combines knowledge of physics, computer science, and mathematics to design models that can predict, simulate, or interpret physical processes. Applications include materials science, quantum mechanics, astrophysics, and more, making it a rapidly growing area of research and industry.

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

To thrive as an Artificial Intelligence Machine Learning Physicist, you need a strong background in physics, advanced mathematics, computer science, and experience with machine learning algorithms, typically supported by a graduate degree in a related field. Proficiency in programming languages such as Python or C++, machine learning frameworks like TensorFlow or PyTorch, and familiarity with data analysis tools are essential, along with experience in scientific computing. Critical thinking, problem-solving, and strong communication skills help you interpret complex data, collaborate across disciplines, and convey research findings effectively. These combined skills are crucial for developing innovative AI models, driving scientific discovery, and advancing technology at the intersection of physics and machine learning.

What collaborative projects can professionals in artificial intelligence machine learning physics expect to work on?

Professionals in Artificial Intelligence Machine Learning Physics often work on interdisciplinary teams, partnering closely with data scientists, physicists, and software engineers. They may contribute to projects such as developing advanced simulation tools, optimizing experimental data analysis, or creating machine learning models to predict physical phenomena. Collaboration is key, as these roles frequently involve integrating AI algorithms with physical models and leveraging domain-specific knowledge from physics experts. This dynamic environment fosters continual learning and offers opportunities to lead innovative research or transition into specialized engineering and research leadership roles.

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

AspectArtificial Intelligence Machine Learning PhysicsData Scientist
Required credentialsDegree in Computer Science, Physics, or related fields; certifications in AI/MLDegree in Statistics, Mathematics, Computer Science; certifications in data analysis
Work environmentResearch labs, tech companies, academia focusing on AI/ML applications in physicsBusiness, finance, healthcare sectors analyzing large datasets
Industry usageDeveloping AI models for physics simulations, research, and technologyExtracting insights from data to inform business decisions

Artificial Intelligence Machine Learning Physics and Data Scientist roles share a focus on data analysis and technical skills. However, AI/ML Physics emphasizes developing algorithms within physics contexts, while Data Scientists focus on analyzing diverse datasets across industries. Both roles often require similar educational backgrounds and certifications, but their applications and work environments differ significantly.

Is artificial intelligence and machine learning a good career?

Artificial Intelligence and Machine Learning are growing fields with high demand for skilled professionals, including roles like AI engineers and data scientists. These careers often require strong programming skills, knowledge of algorithms, and experience with tools like Python and TensorFlow. They offer competitive salaries and opportunities for innovation across various industries.

What cities near Grapevine, TX are hiring for Artificial Intelligence Machine Learning Physics jobs?

Cities near Grapevine, TX with the most Artificial Intelligence Machine Learning Physics job openings:

Executive Director - Applied Artificial Intelligence Machine Learning

Plano, TX • On-site

JPMorgan Chase & Co.
Finance and Insurance • 10K+ employees

Full-time

Medical, Retirement

Re-posted 6 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


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

About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.

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