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$17

How much do internship llm graduate jobs pay per hour?

As of Sep 7, 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 do Internship LLM Graduates do?

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 are the key skills and qualifications needed to thrive as an Internship LLM Graduate?

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.

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.

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Infographic showing various Internship Llm Graduate job openings in the United States as of August 2026, with employment types broken down into 3% As Needed, 74% Full Time, 19% Part Time, 1% Temporary, and 3% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $35,684 per year, or $17.2 per hour.

Campus Graduate Masters Full-Time Engineer - 2027 AI Engineer I, Enterprise Technology Services- New

American Express

Manhattan, NY • On-site

$78K - $124K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 6 days ago

American Express rating

8.6

Company rating: 8.6 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

25th of 154 rated financial services

Job description


At American Express, we empower technologists to learn, innovate, and make an impact from day one. As an AI Engineer I in Enterprise Technology Services, you'll join a full-time graduate program and contribute to technology work that helps teams explore, build, test, and responsibly scale AI-enabled solutions.
In this role, you may support work across machine learning, generative AI, intelligent automation, data pipelines, retrieval patterns, model evaluation, LLM integrations, AI agents, agentic workflows, and AI-enabled software features. You'll collaborate with engineering, product, data, security, risk, and business partners to help deliver enterprise AI solutions responsibly, reliably, and securely.
Responsibilities
  • Support the development, testing, and integration of AI / ML models, LLM integrations, intelligent services, or data retrieval pipelines under guidance.
  • Assist with data collection, preprocessing, transformation, and validation to support model training, testing, evaluation, and implementation.
  • Contribute to debugging and improving AI enabled solutions to strengthen performance, reliability, explainability, maintainability, and quality.
  • Support AI capabilities such as model training workflows, inference endpoints, prompt-based interactions, evaluation routines, retrieval patterns, AI agents, or agentic workflows.
  • Collaborate with engineering, product, data, risk, security, and business partners to implement AI-driven solutions aligned to business requirements.
  • Document model parameters, prompts, assumptions, data pipelines, integrations, and technical decisions to support reproducibility and knowledge sharing.
  • Participate in Agile development practices, including sprint planning, stand-ups, demos, retrospectives, code reviews, and team ceremonies.
  • Assist in ensuring AI systems and AI-enabled features align with enterprise expectations for reliability, safety, governance, security, compliance, and appropriate escalation.

Qualifications
Minimum Qualifications
  • Must have earned a Master's degree in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Computer Engineering, Software Engineering, or another technical field before the end of June 2027.
  • Knowledge of Python and foundational data processing technologies.
  • Foundational understanding of computer science concepts, including data structures, algorithms, object-oriented programming, debugging, testing, and problem solving.
  • Foundational understanding of machine learning concepts such as supervised learning, unsupervised learning, model training, evaluation, feature engineering, and experimentation.
  • Introductory understanding of modern AI systems, including LLM APIs, prompt-based interactions, retrieval patterns, AI powered tools, or generative AI applications.
  • Ability to support AI/ML development, testing, documentation, integration, or data pipeline activities under guidance.
  • Awareness of responsible AI expectations, including reliability, safety, governance, security, privacy, compliance, and appropriate escalation when work is unclear or outside standard guidance.
  • Strong communication, collaboration, documentation, and learning agility with the ability to work effectively across technical and non-technical teams.

Preferred Qualifications
  • Experience through academic coursework, research, projects, open-source contributions, internships, hackathons, or extracurricular activities using Python, R, Java, JavaScript, or similar technologies.
  • Interest in machine learning, generative AI, natural language processing, intelligent automation, data engineering, agentic AI, or AI-enabled software development.
  • Familiarity with NLP techniques and model concepts such as fuzzy matching, embeddings, BERT, transformers, LLMs, or other modern language models.
  • Exposure to LLM APIs or similar AI models, including prompt engineering, prompt evaluation, tools, function calling, retrieval patterns, or agent workflow concepts.
  • Experience or coursework involving machine learning algorithms and applying them to practical or real-world problems.
  • Familiarity with APIs, data pipelines, ETL processes, cloud environments, containerized development, model deployment patterns, or monitoring.
  • Awareness of CI/CD, version control, testing, code reviews, Agile development, and collaborative software engineering workflows.
  • Exposure to version control systems such as Git and collaborative software development workflows.
  • Curiosity for AI powered developer tools, responsible AI practices, governance, security, model documentation, and enterprise-scale delivery.

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.
About Us
At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.
As part of Team Amex, you'll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.
About the Team
We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:
  • Competitive base salaries
  • Bonus incentives
  • 6% Company Match on retirement savings plan
  • Free financial coaching and financial well-being support
  • Comprehensive medical, dental, vision, life insurance, and disability benefits
  • Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
  • 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
  • Free and confidential counseling support through our Healthy Minds program
  • Career development and training opportunities

For a full list of Team Amex benefits, visit our Colleague Benefits Site.
American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.
We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.
US Job Seekers - Click to view the "Know Your Rights" poster. If the link does not work, you may access the poster by copying and pasting the following URL in a new browser window: https://www.eeoc.gov/poster.
The below represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.

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