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Machine Learning Ai Intern Jobs in Dallas, TX (NOW HIRING)

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... Familiarity with latest tools and trends surrounding Large Language Models and Generative AI.

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... Familiarity with latest tools and trends surrounding Large Language Models and Generative AI.

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... Familiarity with latest tools and trends surrounding Large Language Models and Generative AI.

Position Overview We are seeking a motivated DevOps Intern to support the deployment, automation ... AI / MLOps Support * Assist with deployment and monitoring of machine learning and AI applications.

Machine Learning Engineer

Plano, TX · On-site

$120 - $150/hr

Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from ...

Research and Innovation Stay at the forefront of emerging AI and machine learning technologies. Evaluate and integrate new tools, frameworks, and methodologies to enhance model performance and ...

New

Lead Machine Learning Engineer

Plano, TX · On-site

$179 - $205/hr

## Lead Machine Learning EngineerApplylocations: Plano, TX: McLean, VAtime type: Full timeposted on ... Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities ...

New

Showing results 41-60

Machine Learning Ai Intern information

See Dallas, TX salary details

$25.2K

$42.1K

$87.1K

How much do machine learning ai intern jobs pay per year?

As of Aug 21, 2026, the average yearly pay for machine learning ai intern in Dallas, TX is $42,125.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,500.00 per year, depending on experience, location, and employer.

What does a Machine Learning AI Intern do?

A Machine Learning AI Intern assists in developing, testing, and deploying machine learning models and algorithms under the supervision of experienced data scientists or engineers. Typical responsibilities include data preprocessing, feature engineering, model evaluation, and documentation. Interns may also help in researching new AI techniques and supporting the integration of models into existing applications. The role provides hands-on experience with machine learning tools, programming languages like Python, and frameworks such as TensorFlow or PyTorch. This internship helps build foundational skills for a career in artificial intelligence and data science.

What types of projects do Machine Learning AI Interns typically work on during their internship?

As a Machine Learning AI Intern, you can expect to work on real-world projects such as developing predictive models, performing data preprocessing and analysis, or contributing to the improvement of existing algorithms. Interns often assist with tasks like data cleaning, feature engineering, and model evaluation, while collaborating closely with data scientists and engineers. This hands-on experience helps interns build practical skills and gain exposure to the entire machine learning workflow in a professional setting.

What are the key skills and qualifications needed to thrive as a Machine Learning AI Intern, and why are they important?

To thrive as a Machine Learning AI Intern, you need a solid foundation in mathematics, programming (often Python), and machine learning concepts, usually supported by coursework or relevant projects. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is typically expected. Curiosity, problem-solving ability, and strong communication skills help interns collaborate effectively and learn quickly in dynamic environments. These skills are crucial for contributing meaningfully to projects, adapting to new technologies, and growing within the fast-evolving AI field.

What is the difference between Machine Learning Ai Intern vs Data Science Intern?

AspectMachine Learning Ai InternData Science Intern
Required CredentialsRelevant coursework, programming skills, basic understanding of ML conceptsStatistics, programming, data analysis skills, often with similar educational background
Work EnvironmentTech companies, startups, research labs focusing on AI/ML projectsVariety of industries including finance, healthcare, tech, focusing on data analysis
Employer & Industry UsagePrimarily in AI/ML development teams within tech and research sectorsAcross industries for data analysis, reporting, and decision-making support

Machine Learning Ai Interns focus on developing and applying AI and ML models, often working closely with data scientists and engineers. Data Science Interns work on analyzing data, creating reports, and supporting data-driven decisions. While both roles require programming and analytical skills, ML Interns typically specialize in AI algorithms, whereas Data Science Interns focus on broader data analysis tasks.

What cities near Dallas, TX are hiring for Machine Learning Ai Intern jobs?

Cities near Dallas, TX with the most Machine Learning Ai Intern job openings:

Lead Applied AI & Machine Learning Engineer

J.P. Morgan

Plano, TX

Full-time

Medical, Retirement

Posted 6 days ago


Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

Build what's next in enterprise AI - solutions that materially improve how teams make decisions, automate work, and serve internal customers. You will take generative AI from concept to production, help set the standard for semantic consistency across systems, and partner closely with stakeholders to turn complex business needs into measurable outcomes. You will mentor talent and influence technical direction across Corporate Technology and supported Corporate Functions.

As an Applied AI and Machine Learning Lead in the Corporate Technology Data Science and AI team, you will Build what's next in enterprise AI - solutions that materially improve how teams make decisions, automate work, and serve internal customers. In this role, you will take generative AI from concept to production and help set the standard for semantic consistency across systems. You will partner closely with stakeholders to turn complex business needs into measurable outcomes. You will mentor talent and influence technical direction across Corporate Technology and supported Corporate Functions. If you enjoy solving hard problems with real impact, this is the opportunity.

Job Responsibilities

  • Build generative AI, agentic AI, and large language model solutions in Python from proof of concept through production deployment with measurable outcomes
  • Design context engineering approaches to improve model accuracy, latency, reliability, and end-to-end user experience
  • Lead enterprise semantic modeling strategy, including ontology standards, governance practices, and lifecycle management
  • Partner with domain experts to create scalable ontologies that represent business entities, relationships, rules, and constraints
  • Define semantic integration patterns across data pipelines, application programming interfaces (APIs), data contracts, and experience layers to resolve semantic conflicts
  • Establish and govern a unified semantic layer that enables trusted analytics across business intelligence, machine learning, and transactional systems
  • Enable intelligent workflows and AI agents using ontology-driven context, semantic reasoning, and orchestration approaches
  • Build and maintain pipelines and frameworks for model training, evaluation, optimization, monitoring, and machine learning operations
  • Implement responsible AI practices, model risk controls, and governance aligned to regulated environments
  • Mentor engineers and data scientists, raising the bar on engineering rigor, reuse, and continuous improvement across the team

Required Qualifications, Capabilities, and Skills

  • Master's degree in a data science-related discipline and eight years of industry experience, or PhD in a data science-related discipline
  • Demonstrated experience developing and deploying machine learning and generative AI solutions using Python
  • Proven ability to write and maintain production-quality code, including documentation and maintainable design patterns
  • Experience building automated testing practices, including unit tests, and implementing continuous integration pipelines
  • Experience building and managing data pipelines and processing workflows for analytics and machine learning use cases
  • Strong scientific thinking and structured problem-solving skills, including hypothesis-driven analysis and metric definition
  • Strong written and verbal communication skills, with the ability to explain complex concepts to technical and non-technical stakeholders
  • Demonstrated ownership and attention to detail when operating in ambiguous, complex problem spaces
  • Ability to work independently while collaborating effectively across product, engineering, data, and business partners

Preferred Qualifications, Capabilities, and Skills

  • Experience designing or governing semantic models and ontologies, including taxonomy design and lifecycle governance
  • Experience implementing retrieval-augmented generation, tool use, and evaluation strategies for large language model applications
  • Familiarity with responsible AI techniques, including bias testing, explainability approaches, and model monitoring standards
  • Experience designing scalable architectures for real-time or near-real-time inference and intelligent workflow orchestration
  • Experience influencing cross-functional technical direction and mentoring engineers through design reviews and delivery execution

#LI-RB3

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

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.