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How much do internship llm jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for internship llm 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 are Internship LLMs?

Internship LLMs typically refer to internship positions designed for students currently pursuing or recently graduated with a Master of Laws (LLM) degree. These internships provide practical legal experience, allowing LLM students to apply their academic knowledge in real-world settings, such as law firms, corporations, non-profits, or government agencies. The goal is to help interns build professional networks, develop specialized skills, and enhance their employability in the legal field. Most LLM internships are short-term and may focus on specific areas of law that align with the intern's interests and coursework.

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

To thrive in an LLM Internship, you typically need a background in computer science, machine learning, or a related field, with strong programming skills in Python and a solid understanding of natural language processing concepts. Familiarity with deep learning frameworks like TensorFlow or PyTorch, and experience with version control systems such as Git, are commonly required. Strong problem-solving abilities, effective communication, and a collaborative mindset will help you stand out in a research or development team. These skills and qualities are important for contributing to cutting-edge AI projects and adapting to the rapidly evolving field of language models.

What types of projects do interns typically work on during an LLM internship, and how do they contribute to the team's goals?

During an LLM (Large Language Model) internship, interns are often assigned to projects that involve data preprocessing, model evaluation, or contributing to the development of NLP applications. Interns may assist in curating datasets, fine-tuning models, or building tools that help improve the performance or usability of LLMs. These tasks are integral to the team's objectives, as interns' contributions help accelerate research, streamline workflows, and ultimately improve product outcomes. Collaboration is common, with interns working closely with engineers, researchers, and product managers to solve real-world challenges.
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2026 Fall Intern, ML/NLP Research

Samsung Research America Internship

Mountain View, CA • On-site

Other

Posted yesterday

Job description

Lab Summary:AI Research Center (AIC) located in Mountain View, California focuses on research and development which directly impacts future Samsung products reaching hundreds of millions of users worldwide. We are focused on pushing the state-of-the-art and practice in natural language and knowledge intelligence. 

Position Summary: Samsung Research AI center, located in Mountain View, CA, is currently recruiting world-class students who can thrive in a fast-pace, cross team, results-driven environment, with focus on highly visible, challenging, and cross discipline projects. You will be part of an exciting project to build an adaptive, personalized, contextual and secure AI model and system to enable fast, accurate and safe interactions tailored to users' needs on Samsung devices. 

Position Responsibilities: We are looking for Fall Interns (Flexible start date for a 3 month internship between September-December).

  • Develop and implement novel deep learning/reinforcement learning algorithms for natural language processing (text, speech) in various applications 
  • Contribute to the research activities of our team 
  • Generate creative solutions (patents) and publish in top conferences (papers) 

Required Skills: 

  • Current Ph.D. student in CS, EE, or related field 
  • Experience in one or more of the following areas:  
    • Expertise in LLM including model architecture, training/finetuning techniques, retrieval augmented generation (RAG), reasoning and action planning, etc.
    • Experience in planning, tool use, agent AI, and agent memory to develop autonomous systems for decision-making, problem-solving, and adaptability. 
    • Experience in knowledge augmented AI technologies (e.g., language prompt, knowledge graph, neuro-symbolic learning)
    • Experience in conversational AI technologies: natural language processing (e.g., language models, semantic parsing, natural language generation etc.), dialogue (e.g., state tracking, policy learning), and representation learning (embedding, conceptualization, etc.)
    • Experience in multimodal AI technologies for various multimodal applications
    • Experience in on-device AI technologies such as lightweight model architecture design
  • Teamwork and communication skills 
  • Proficiency in a neural network library (e.g., PyTorch, TensorFlow)
  • Track record of research/publications on machine learning and artificial intelligence field (NeurIPS, ICML, ICLR, AAAI, IJCAI, CVPR, ACL, EMNLP, NAACL, TACL, etc.) 

Apply