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Internship Large Language Model Llm Jobs (NOW HIRING)

... Large Language Model (LLM) solution to check coherence and consistency. Resource will also develop and modify existing models related to customer long term engagement and retention. This role will ...

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How much do internship large language model llm jobs pay per hour?

As of Jun 22, 2026, the average hourly pay for internship large language model llm in the United States is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What types of projects do interns typically work on during a Large Language Model (LLM) internship?

During a Large Language Model (LLM) internship, interns often participate in projects such as data preprocessing, fine-tuning models on specific tasks, evaluating model outputs, and developing tools for model interpretability. Interns may collaborate closely with research scientists and engineers, contributing to both experimental and production-level code. These projects provide practical experience with natural language processing pipelines and exposure to the latest advancements in AI, making it a valuable learning opportunity for those interested in a career in machine learning and artificial intelligence.

What are the key skills and qualifications needed to thrive as an Internship Large Language Model (LLM) specialist, and why are they important?

To thrive as an Internship Large Language Model (LLM) specialist, you need a solid grasp of machine learning fundamentals, natural language processing, and proficiency in programming languages like Python, often supported by coursework or research in computer science or related fields. Familiarity with tools such as TensorFlow, PyTorch, Hugging Face Transformers, and experience using cloud platforms are typically required. Strong analytical thinking, problem-solving abilities, and effective communication help you collaborate with teams and present complex ideas clearly. These competencies are crucial for developing, evaluating, and refining LLMs to create impactful AI solutions.

What is an Internship in Large Language Model (LLM)?

An Internship in Large Language Model (LLM) typically involves working with advanced artificial intelligence models like GPT or similar technologies. Interns in this field assist with tasks such as data preparation, model training, evaluation, and deployment of natural language processing applications. They may also contribute to research, experimentation, and development of new model features or performance improvements. This role provides hands-on experience in AI, machine learning, and natural language processing, often requiring knowledge of programming, data science, and AI concepts.

What is the difference between Internship Large Language Model Llm vs Data Scientist Intern?

AspectInternship Large Language Model LlmData Scientist Intern
Required CredentialsRelevant coursework, programming skills, knowledge of NLPStatistics, programming, data analysis
Work EnvironmentAI research labs, tech companies, startupsData analysis teams, tech firms, research institutions
Employer & Industry UsageAI development, NLP projects, machine learningData analysis, predictive modeling, business insights

Both roles involve data and programming skills, but Internship Large Language Model Llm focuses on natural language processing and AI model development, while Data Scientist Interns work on analyzing data to generate insights. The choice depends on your interest in AI/NLP versus data analysis and business applications.

More about Internship Large Language Model Llm jobs
What cities are hiring for Internship Large Language Model Llm jobs? Cities with the most Internship Large Language Model Llm job openings:
What are the most commonly searched types of Large Language Model Llm jobs? The most popular types of Large Language Model Llm jobs are:
What states have the most Internship Large Language Model Llm jobs? States with the most job openings for Internship Large Language Model Llm jobs include:
Infographic showing various Internship Large Language Model Llm job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 92% Full Time, 5% Part Time, and 2% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.
Data Scientist, Senior

$114K/yr

Full-time

Posted 10 days ago


Arizona State University rating

7.6

Company rating: 7.6 out of 10

Based on 87 frontline employees who took The Breakroom Quiz

242nd of 539 rated colleges and universities


Job description

Job Profile:
Business and Data Analyst 3
Job Family:
Business and Data Analytics
Time Type:
Full time
Max Pay - Depends on experience:
$114,000.00 USD Annual
Apply before 11:59 PM Arizona time the day before the posted End Date.
Minimum Qualifications:
Bachelor's degree and five (5) years of experience appropriate to the area of assignment/field; OR, Any equivalent combination of experience and/or training from which comparable knowledge, skills and abilities have been achieved.
Job Profile Summary:
Defines systems requirements, makes recommendations for technology selection, and performs moderately complex data analysis to ensure data management objectives within a work unit are met.
Job Description:
Supports ASU's Actionable Analytics initiatives through the application of advanced data science, machine learning, statistical analysis, and artificial intelligence techniques, including the use of large language models (LLMs) and other foundation model technologies. Serves as a senior-level contributor responsible for designing, developing, validating, deploying, and monitoring analytical and AI-enabled solutions that address operational and strategic organizational needs.
Position Salary Range:
  • $90,000 - $114,000 per year, DOE

Essential Duties:
  • Leverages machine learning, artificial intelligence, large language models (LLMs), and other advanced analytical techniques to develop innovative solutions that address operational and strategic institutional needs.
  • Promotes the responsible, ethical, secure, and compliant use of data science, machine learning, and artificial intelligence technologies in accordance with institutional policies and applicable regulations.
  • Determines and develops advanced research design methodologies, data analysis approaches, statistical modeling procedures, machine learning solutions, and generative AI applications to meet operational and strategic organizational needs.
  • As part of a team, conducts all phases of analytics, machine learning, and AI solution development, including data acquisition and extraction, data cleaning, data exploration, feature engineering, prompt engineering, model development, model validation/testing deployment, monitoring, evaluation, and ongoing support.
  • Selects and applies advanced statistical, predictive modeling, machine learning, large language model (LLM), and generative AI techniques to generate actionable insights and address complex organizational challenges using structured and unstructured data sources.
  • Develops, deploys, integrates, and maintains statistical models, machine learning models, and AI-enabled solutions, including applications leveraging large language models (LLMs), foundation models, and retrieval-augmented generation (RAG) techniques in development and production environments.
  • Implements monitoring and evaluation processes for statistical models, machine learning models, and AI-enabled solutions to assess performance and enable continuous improvement.
  • Collaborates with technical and non-technical stakeholders to translate business needs into analytical solutions and actionable recommendations.
  • Creates and maintains technical documentation, analytical workflows, and model documentation.
  • Supports the adoption of machine learning operationalization (MLOps/AIOps) practices, including version control, model deployment, workflow automation, and reproducibility.
  • Learns, evaluates, and adopts new analytical methodologies, technologies, and tools to meet changing organizational needs.
  • Presents analytical findings and recommendations through written reports, presentations, and data visualizations to technical and non-technical stakeholders.
  • Provides technical guidance and mentorship to junior staff members and project teams as appropriate.

Desired Qualifications:
  • Demonstrated knowledge of and experience applying generative AI and large language model (LLM) technologies, using a wide-ranging suite of structured and unstructured data sources and success outcomes, as well as advanced traditional and modern/machine learning predictive modeling methodologies.
  • Experience conducting all phases of analytics, machine learning, and AI solution development, including data acquisition and extraction, data cleaning, data exploration, feature engineering, prompt engineering, model development, model validation/testing, deployment, monitoring, evaluation, and ongoing support.
  • Experience developing, validating, deploying, and maintaining machine learning models and AI-enabled applications, including solutions leveraging large language models (LLMs), foundation models, and retrieval-augmented generation (RAG) techniques in cloud or production environments.
  • Demonstrated knowledge of machine learning and AI best practices, including cross-validation, hyperparameter tuning, prompt optimization, model monitoring, performance evaluation, explainability, and responsible AI principles.
  • Experience evaluating, selecting, and applying large language models (LLMs), foundation models, and generative AI technologies to support knowledge discovery, workflow automation, decision support, and business process improvement.
  • Proficiency in Python and SQL, including experience leveraging libraries, frameworks, and APIs used for machine learning, data science, and generative AI applications.
  • Demonstrated working knowledge of higher education data systems, including specialized data mining, natural language processing, knowledge discovery, and data visualization techniques.
  • Experience using cloud-based analytics, machine learning, and AI services to develop, deploy, monitor, and support analytical and AI-enabled solutions.
  • Experience using version control systems and collaborative development tools.
  • Experience using data visualization tools and techniques to communicate complex analytical findings and insights.
  • Demonstrated ability to clearly and accurately summarize findings and recommendations to technical and non-technical stakeholders to inform decision making.
  • Demonstrated ability to lead complex analytical projects, prioritize competing demands, and complete projects on time and within scope.
  • Demonstrated ability to work effectively both independently and collaboratively as part of a team.
  • Demonstrated ability to translate stakeholder needs into appropriate, functional, and informative analytical and AI-enabled solutions.
  • Experience mentoring or providing technical guidance to analysts, data scientists, or project teams.

Working Environment:
  • Activities are performed in an environmentally controlled office setting subject to extended periods of staying in a stationary position, manipulating a computer 75 percent; required to traverse moderate distances to perform work 10 percent. Ability to clearly express oneself and effectively exchange information to perform essential functions. Frequent moving, transporting, and positioning up to 25 pounds 15 percent. Regular activities require ability to quickly change priorities, which may include or are subject to resolution of conflicts.

Department Statement:
Actionable Analytics, within the Office of the University Provost, advances studentsuccess by developing and supporting innovative enterprise analytics applications anddata solutions for the Academic Enterprise. The department provides trusted data, datascience solutions, actionable insights, and decision support tools that empower studentsuccess initiatives for ASU campus-immersion and digital-immersion students.
Driving Requirement:
Driving is not required for this position.
Location:
Campus: Tempe
Funding:
No Federal Funding
Instructions to Apply:
Current employees, student workers seeking staff opportunities, and students applying for student worker positions must apply directly through the Workday Jobs Hub.
Please use the link below to log in using single sign-on.
https://www.myworkday.com/asu/d/inst/1$9925/9925$23236.htmld
To be considered, your application must include all of the following attachments:
  • Cover letter
  • Resume or CV

Multiple documents may be uploaded in the attachments section. Alternatively, applicants may combine all required materials into a single PDF for submission. Please ensure uploaded documents are clearly labeled and include your name.
Please ensure your resume includes all employment information in month and year format, for example 6/04 to 8/14, along with job title, job duties, and employer name for each position. Your resume should clearly demonstrate how your experience and background meet the minimum and desired qualifications for this position. Incomplete applications or missing required materials may not be considered.
Important: Do not withdraw your application to make edits. Once an application is withdrawn, it cannot be edited, reactivated, or replaced with a new submission. If you have questions or need assistance, please contact The Office of Human Resources Talent Acquisition before the posting close date.
Graduate Assistant, Intern and part-time positions are counted as half time for experience equivalency, meaning one year equals six months of experience.
Only electronic applications will be accepted for this position. By submitting an application, you confirm that the information provided is accurate and complete.
ASU Statement:
Arizona State University is a new model for American higher education, an unprecedented combination of academic excellence, entrepreneurial energy and broad access. This New American University is a single, unified institution comprising four differentiated campuses positively impacting the economic, social, cultural and environmental health of the communities it serves. Its research is inspired by real world application blurring the boundaries that traditionally separate academic disciplines. ASU serves more than 100,000 students in metropolitan Phoenix, Arizona, the nation's fifth largest city. ASU champions inclusive excellence, and welcomes students from all fifty states and more than one hundred nations across the globe.
ASU is a tobacco-free university. For details visit https://wellness.asu.edu/explore-wellness/body/alcohol-and-drugs/tobacco
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, or any other basis protected by law.
Notice of Availability of the ASU Annual Security and Fire Safety Report:
In compliance with federal law, ASU prepares an annual report on campus security and fire safety programs and resources. ASU's Annual Security and Fire Safety Report is available online at https://www.asu.edu/police/PDFs/ASU-Clery-Report.pdf. You may request a hard copy of the report by contacting the ASU Police Department at 480-965-3456.
Relocation Assistance - For information about schools, housing child resources, neighborhoods, hospitals, community events, and taxes, visit https://cfo.asu.edu/az-resources.
Employment Verification Statement:
ASU conducts pre-employment screening which may include verification of work history, academic credentials, licenses, and certifications.
Background Check Statement:
ASU conducts pre-employment screening for all positions which includes a criminal background check, verification of work history, academic credentials, licenses, and certifications. Employment is contingent upon successful passing of the background check.
Fingerprint Check Statement:
This position is considered safety/security sensitive and will include a fingerprint check. Employment is contingent upon successful passing of the fingerprint check.

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