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Internship Llm Graduate Jobs (NOW HIRING)

Generative AI Engineering Intern (Graduate)

$17.25 - $22.25/hr

Interns can support 100% remotely. This open-ended graduate internship is designed to provide ... Hands-on experience with LLM frameworks such as LangChain, LlamaIndex, or Hugging Face Transformers.

$78K - $82K/yr

D, and Humphrey Fellowship Programs,3.) JD and graduate law students from outside of the US ... Gather information about job and hiring trends and cultivate internship and employment ...

Responsibilities We are seeking exceptional graduate students to join our AI Lab as Research Interns in San Francisco. You'll work on fundamental problems in LLM-based agentic systems and efficient ...

Intern, AI Engineering

San Francisco, CA · On-site

$19.75 - $25.50/hr

Responsibilities We are seeking exceptional graduate students to join our AI Lab as Research Interns in San Francisco. You'll work on fundamental problems in LLM-based agentic systems and efficient ...

Intern, AI Engineering

San Francisco, CA

$19.75 - $25.50/hr

Responsibilities We are seeking exceptional graduate students to join our AI Lab as Research Interns in San Francisco. You'll work on fundamental problems in LLM-based agentic systems and efficient ...

... graduate program in CS, data science, engineering, or related field BONUS POINTS Prior internship ... LLM evals An active GitHub, portfolio, or side project that shows what you can do WHY SCALE AI ...

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Internship Llm Graduate information

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$17

How much do internship llm graduate jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for internship llm graduate in the United States is $17.16, according to ZipRecruiter salary data. Most workers in this role earn between $17.07 and $17.31 per hour, depending on experience, location, and employer.

What is an Internship LLM Graduate?

An Internship LLM Graduate is an individual who has recently completed a Master of Laws (LLM) degree and is participating in an internship to gain practical legal experience. These internships are typically designed to provide recent LLM graduates with exposure to real-world legal work, such as research, drafting documents, and assisting with case preparation. The role helps bridge the gap between academic studies and professional practice, often improving employment prospects and providing valuable industry contacts. LLM graduates may intern at law firms, corporate legal departments, government agencies, or non-profit organizations.

What types of projects and responsibilities can an Internship LLM Graduate expect to work on during their internship?

As an Internship LLM Graduate, you will typically assist with legal research, draft memos or briefs, and support case preparation under the supervision of experienced attorneys. You may also attend client meetings, participate in internal discussions, and observe court proceedings, depending on your placement. This hands-on experience helps you develop practical legal skills and gain insight into specific areas of law, such as corporate, intellectual property, or litigation. Collaboration with both legal and administrative teams is common, fostering a well-rounded understanding of the legal profession.

What is the difference between Internship Llm Graduate vs Legal Assistant?

AspectInternship Llm GraduateLegal Assistant
Required CredentialsLLM degree, legal research skillsAssociate degree or paralegal certification, legal knowledge
Work EnvironmentLaw firms, legal departments, academic settingsLaw firms, corporate legal departments, government agencies
Employer & Industry UsageInternship for skill development, often temporarySupport role in legal teams, ongoing employment
Common Search & Comparison IntentUnderstanding internship roles for law graduatesLegal support roles for legal professionals

In summary, an Internship Llm Graduate is typically a temporary position aimed at gaining practical experience during or after completing an LLM degree, often in academic or law firm settings. A Legal Assistant is a more permanent support role requiring legal knowledge and assisting lawyers with case preparation and research. Both roles are integral to legal work but differ in duration, responsibilities, and career stage.

What are the key skills and qualifications needed to thrive as an Internship LLM Graduate, and why are they important?

To thrive as an Internship LLM Graduate, you need a solid understanding of legal principles, research skills, and advanced academic qualifications such as a Master of Laws (LLM) degree. Familiarity with legal databases (e.g., Westlaw, LexisNexis), document management systems, and citation tools is typically required. Strong analytical thinking, attention to detail, and effective written and verbal communication are crucial soft skills in this role. These competencies enable you to contribute meaningful legal insights, support casework, and excel in a competitive legal environment.
More about Internship Llm Graduate jobs
What cities are hiring for Internship Llm Graduate jobs? Cities with the most Internship Llm Graduate job openings:
What are the most commonly searched types of Llm Graduate jobs? The most popular types of Llm Graduate jobs are:
What states have the most Internship Llm Graduate jobs? States with the most job openings for Internship Llm Graduate jobs include:
Infographic showing various Internship Llm Graduate job openings in the United States as of July 2026, with employment types broken down into 2% As Needed, 77% Full Time, 19% Part Time, and 2% Contract. Highlights an 98% Physical, and 2% Remote job distribution, with an average salary of $35,684 per year, or $17.2 per hour.
Graduate Intern - LLM Reliability and Uncertainty for AI Science Assistants

Graduate Intern - LLM Reliability and Uncertainty for AI Science Assistants

The National Renewable Energy Laboratory (NREL)

Golden, CO • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 7 days ago


Job description

Posting Title
Graduate Intern - LLM Reliability and Uncertainty for AI Science Assistants
Location
CO - Golden
Position Type
Intern (Fixed Term)
Hours Per Week
40
Working at NLR
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.
Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.
At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.
Job Description
The AI, Learning and Intelligent Systems group in the NLR Computational Science Center has an opening for a graduate student researcher in LLM Reliability and Uncertainty for AI Science Assistants. The researcher will investigate methods for quantifying uncertainty in LLM-based science assistants over multi-turn scientific dialogue, with an emphasis on flagging when a scientific question or task is underspecified or ill-posed. In practice, scientific questions can be vague, open-ended, or underdetermined. LLM-based assistants can quietly insert their own assumptions into such requests to fill the gap instead of raising concerns to their human counterpart. This internship will investigate if the assistant's internal representations can be probed to detect these instances so they may be flagged for the user or used to trigger clarifying questions. We are looking for a dynamic, motivated researcher with a strong technical background and an interest in AI for science, uncertainty-aware machine learning, human-AI scientific workflows, and trustworthy AI. The successful candidate must be able to work at the intersection of machine learning research and practical AI system integration.
Responsibilities include:
  • Research and evaluate uncertainty quantification and hallucination detection methods for multi-turn, agentic scientific workflows
  • Develop probing methods that predict, from a model's internal representations, when a scientific task specification is incomplete or inconsistent and a clarifying question is warranted
  • Build and instrument evaluation pipelines that capture and analyze model internal states over multi-turn scientific dialogue on HPC systems
  • Conduct experiments and analyze model behavior across computational science domains and established benchmarks
  • Contribute to technical documentation, research reports, publications, and presentations summarizing project progress and findings
  • Develop, test, and maintain high-quality research code and evaluation pipelines

Basic Qualifications
Minimum of a 3.0 cumulative grade point average.
Undergraduate: Must be enrolled as a full-time student in a bachelor's degree program from an accredited institution.
Post Undergraduate: Earned a bachelor's degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate: Must be enrolled as a full-time student in a master's degree program from an accredited institution.
Post Graduate: Earned a master's degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master's degree and enrolled as PhD student from an accredited institution.
Please Note:
• Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process.
• If selected for position, a letter of recommendation will be required as part of the hiring process.
• Must meet educational requirements prior to employment start date.
* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
  • Familiarity with large language models, including agentic, tool-using, or multi-turn conversational LLM systems
  • Experience developing or evaluating machine learning models for classification, uncertainty estimation, or related tasks
  • Knowledge of probabilistic machine learning or uncertainty quantification concepts
  • Hands-on experience with open-weight LLMs and modern deep learning frameworks
  • Experience running Python code on HPC or multi-GPU systems
  • Strong software engineering and debugging skills
  • Ability to work independently while collaborating effectively in a multidisciplinary research environment

Preferred Qualifications
  • Research experience related to hallucination detection, uncertainty quantification, interpretability, explainability, or trustworthy AI
  • Familiarity with representation probing or mechanistic interpretability methods
  • Experience with LLM benchmarking and evaluation, including multi-turn or conversational agent evaluation and LLM-as-a-judge protocols
  • Experience with scientific question-answering systems, AI for science applications, or scientific agent frameworks
  • Coursework or research background in a computational science domain (e.g., fluid mechanics, solid mechanics, materials science, or numerical methods for PDEs)

Job Application Submission Window
The anticipated closing window for application submission is up to 30 days and may be extended as needed.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: / Annual Salary Range: $44,500 - $71,200
NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.
Benefits Summary
Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.
* Based on eligibility rules
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement.
Drug Free Workplace
NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
Submission Guidelines
Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
Reasonable Accommodations
E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish.
E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.