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Internship Large Language Model Llm Jobs (NOW HIRING)

Nvidia

OR · On-site

$98.40K - $125.40K/yr

We are now looking for a Senior Research Scientist passionate about Large Language Model (LLM) and Diffusion Language Model (DLM) post-training and system optimization. Are you excited to shape the ...

Pearson Education

Staff Software Engineer - AI

Hoboken, NJ · On-site

$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 ...

Purple Drive Technologies

Gen AI architect

Mclean, VA · On-site

$63.75 - $84/hr

Lead the implementation of Large Language Model (LLM)-based systems and GenAI-powered applications. * Design and implement AI agents using frameworks such as LangChain. * Develop and integrate Model ...

Pearson Education

Staff Software Engineer - AI

Hoboken, NJ · On-site

$150K - $165K/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 ...

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

As of May 30, 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 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 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 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.

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Internship Large Language Model Llm jobs near you
Infographic showing various Internship Large Language Model Llm job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 79% Full Time, 19% Part Time, and 1% Temporary. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.
Software Engineer (Language Modeling), BS+12 yrs

Software Engineer (Language Modeling), BS+12 yrs

Link, LLC

Columbia, MD • On-site

Full-time

Posted 9 days ago

Job description

Description: We are seeking a highly skilled and motivated Sr. LLM Engineer to join our team in driving the advancement of our Language Model infrastructure. As a key member of our AI/ML team, you will be responsible for the training, hosting, and optimization of Large Language Model (LLM) instances within our compute environment. The ideal candidate should possess a strong passion for pushing the boundaries of language technology, a deep understanding of LLM architectures, and the grit to tackle complex challenges head-on. This role requires a self-reliant individual with a drive to identify and fix inefficiencies, constantly striving to improve the codebase and optimize model performance. If you thrive in a fast-paced environment and have an unwavering commitment to delivering cutting-edge language solutions, this position is for you.
Responsibilities:
• Design, develop, and maintain the infrastructure for training, hosting, and serving LLM instances.
• Optimize model training pipelines to achieve high performance and resource efficiency.
• Implement and integrate state-of-the-art LLM architectures and techniques.
• Collaborate with cross-functional teams to understand business requirements and deliver impactful language solutions.
• Monitor and analyze model performance metrics, identifying areas for improvement and implementing optimizations.
• Develop and maintain documentation, best practices, and coding standards for LLM development and deployment.
• Stay up-to-date with the latest advancements in LLM research and industry trends, and incorporate them into our projects.
• Mentor and guide junior engineers, fostering a culture of continuous learning and knowledge sharing.
Skills Requirements:
• 12+ years of experience in software engineering, with a focus on machine learning or natural language processing.
• Degree in Computer Science, Artificial Intelligence, or a related field.
• Strong expertise in deep learning frameworks such as TensorFlow, PyTorch, or MXNet.
• Proficiency in programming languages such as Python, C++, or Java.
• Solid understanding of LLM architectures, training techniques, and evaluation methodologies.
• Familiarity with cloud platforms (e.g., AWS, GCP) and their machine learning services.
• Knowledge of software engineering best practices, including version control, testing, and continuous integration/deployment.
• Excellent problem-solving and debugging skills.
• Strong communication and collaboration abilities to work effectively with cross-functional teams.
Nice to Haves:
• Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, or a related field.
• Proven track record of implementing and deploying large-scale LLM systems in production environments.
• Experience with distributed computing frameworks like Apache Spark or Hadoop.
• Experience with natural language understanding, generation, and dialogue systems.
• Familiarity with techniques such as transfer learning, few-shot learning, and reinforcement learning.
• Contributions to open-source projects or research publications in the field of LLMs.
• Experience with serving models using APIs and building scalable inference pipelines.
• Knowledge of DevOps practices and tools like Docker, Kubernetes, and Jenkins.
YOE Requirement: 12 yrs., B.S. in a technical discipline or 4 additional yrs. in place of B.S.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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