1

Internship Large Language Model Llm Jobs (NOW HIRING)

NLP (Natural Language Processing) Generative AI & Large Language Models (LLM) Python Skills * Educational Qualifications: Graduate or Doctorate degree in information technology, Neuroscience ...

Data Engineer

Cincinnati, OH · On-site

$109K - $132K/yr

RAG Type LLM Workflows: * Develop and maintain data pipelines specifically tailored for Retrieval-Augmented Generation (RAG) type Large Language Model (LLM) workflows. * Ensure efficient data ...

About the role We're seeking an experienced engineer to deploy enterprise-grade AI solutions, focusing on Retrieval-Augmented Generation (RAG) pipelines and large language model (LLM) workflows. This ...

About the role We're seeking an experienced engineer to deploy enterprise-grade AI solutions, focusing on Retrieval-Augmented Generation (RAG) pipelines and large language model (LLM) workflows. This ...

Staff Software Engineer - AI

Hoboken, NJ · Hybrid

$150K - $180K/yr

Develop and integrate at least one Large Language Model (LLM) into production workflows. * Design and implement Retrieval-Augmented Generation (RAG) pipelines. * Apply advanced prompt engineering ...

next page

Showing results 1-20

Internship Large Language Model Llm information

See salary details

$9

$17

$23

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

As of Jun 23, 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.

Full-time

Posted yesterday


Job description

Job Summary
We are seeking an experienced GenAI / NLP Developer with strong Python and deep learning expertise to design, develop, and deploy Large Language Model (LLM)-based solutions. The role focuses on Generative AI, NLP applications, vector databases, and modern AI frameworks, with exposure to cloud platforms and agentic architectures.
Key Responsibilities
  • Develop, fine-tune, and deploy LLM-based applications using Python.
  • Implement Generative AI solutions using prompt engineering techniques and vector databases.
  • Build, train, and optimize NLP models including text classification, sentiment analysis, and summarization.
  • Utilize frameworks such as LangChain or similar tools for LLM orchestration.
  • Support rapid application development using Streamlit, FastAPI, or Flask.
  • Collaborate with cross-functional teams in an Agile development environment.

Required Skills & Experience
  • 6+ years of overall experience in software development, data analytics, or data science.
  • 2+ years of hands-on experience with deep learning, NLP, and GenAI technologies.
  • Strong proficiency in Python programming.
  • Experience with deep learning frameworks such as TensorFlow and PyTorch.
  • Hands-on experience with Hugging Face Transformers.
  • Practical experience with vector databases and prompt engineering.
  • Solid understanding of Large Language Models (LLMs) and real-world AI applications.
  • Experience deploying AI/ML solutions on Azure or GCP (preferred).
  • Knowledge of agentic or multi-agent architectures (e.g., AutoGen) is a plus.
  • Healthcare domain knowledge is a plus.

Competencies
  • Strong problem-solving and analytical skills
  • Ability to work independently and in collaborative Agile teams
  • Excellent communication and documentation skills
  • Innovative mindset with focus on practical AI solutions

Preferred Skills
  • Experience with AI & GenAI solutions for Business Process Services (BPS)
  • Exposure to cloud-native AI deployments
  • Familiarity with rapid prototyping and proof-of-concept development