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Intern Llm Trainer Jobs (NOW HIRING)

Veeam Software

AI/ML Intern Summer 2027

San Jose, CA · On-site

$40 - $50/hr

As a Summer Intern, you'll participate in a comprehensive onboarding experience led by our ... LLM Experience: Experience training, fine-tuning, or evaluating transformer models or LLMs.

KPMG LLP

Learn about changes in tax law (through KPMG provided training and materials, as well as ... or LLM in Taxation, or equivalent program * Upon completion of this internship, candidates must ...

KPMG LLP

Learn about changes in tax law (through KPMG provided training and materials, as well as ... or LLM in Taxation, or equivalent program * Upon completion of this internship, candidates must ...

KPMG LLP

Learn about changes in tax law (through KPMG provided training and materials, as well as ... or LLM in Taxation, or equivalent program * Upon completion of this internship, candidates must ...

KPMG LLP

Learn about changes in tax law (through KPMG provided training and materials, as well as ... or LLM in Taxation, or equivalent program * Upon completion of this internship, candidates must ...

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Intern Llm Trainer information

What does an Intern LLM Trainer do?

An Intern LLM Trainer assists in training large language models (LLMs) by curating datasets, annotating data, and evaluating model outputs. They work closely with machine learning engineers and data scientists to improve the accuracy and performance of AI models. This role often involves researching new methods, running experiments, and providing feedback to enhance natural language understanding. Interns may also help document processes and support model deployment in real-world applications.

What are some typical responsibilities and learning opportunities for an Intern LLM Trainer during their internship?

As an Intern LLM Trainer, you will typically assist in preparing and curating training datasets, annotating data, and running model evaluations under the guidance of senior machine learning engineers. You'll also gain hands-on experience in fine-tuning large language models (LLMs) and analyzing their performance. This role offers the opportunity to learn best practices in prompt engineering, collaborate with data scientists and software engineers, and gain exposure to the latest advancements in natural language processing. Regular feedback and mentorship are common, helping you develop both technical and teamwork skills.

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

To thrive as an Intern LLM Trainer, you should have a solid understanding of natural language processing, machine learning fundamentals, and strong programming skills, often supported by coursework or experience in computer science or related fields. Familiarity with tools like Python, PyTorch or TensorFlow, and version control systems such as Git is typically required, along with exposure to data labeling platforms. Attention to detail, strong analytical thinking, and effective communication are vital soft skills for collaborating on model improvement and troubleshooting. These competencies enable interns to contribute meaningfully to the development and refinement of language models, ensuring high-quality outcomes and impactful learning experiences.

What is the difference between Intern Llm Trainer vs Data Annotator?

AspectIntern Llm TrainerData Annotator
Required CredentialsBasic understanding of machine learning, NLP, or AI; often pursuing related degreesHigh school diploma or equivalent; no specialized credentials typically needed
Work EnvironmentTech companies, AI startups, research labs; collaborative and project-basedData labeling firms, tech companies; focused on data preparation tasks
Employer & Industry UsageAI development, machine learning teams, research projectsData management, AI training datasets, quality assurance

Intern Llm Trainers focus on training language models through supervised learning and require some technical knowledge, while Data Annotators primarily label data to prepare datasets. Both roles are essential in AI development but differ in technical complexity and responsibilities.

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What are popular job titles related to Intern Llm Trainer jobs?

For Intern Llm Trainer jobs, the most frequently searched job titles are:

Intern AI Engineer, Early-Career - LLM Context & Data Layer (Healthcare)

Remote

Cotiviti
Health Care and Social Assistance • 5 - 10K employees
Learn more about Cotivitiexternal

Full-time

Posted 19 days ago

Cotiviti rating

8.3

Company rating: 8.3 out of 10

Based on 33 frontline employees who took The Breakroom Quiz

Job description

Overview
We are seeking an Intern-AI Engineer to help design, build, and deploy AI-powered applications that leverage large language models (LLMs) and enterprise data systems. This role focuses on developing practical AI solutions that improve healthcare treatment, payment, and operations through intelligent systems and natural language interfaces.
You will work closely with Data Scientists, Data Engineers, and business stakeholders to build the underlying architecture for AI agents - including context layers, data retrieval systems, and governance guardrails - that operate reliably in regulated, data-intensive healthcare environments. This is an excellent opportunity for an early-career engineer passionate about AI technologies and building real-world applications that scale.
We are currently looking for interns who can start immediately, 12-week internship, and work 40 hours per week.
Responsibilities
Technical Expertise
  • SQL fundamentals - comfortable writing queries against structured data, not just describing them
  • Exposure to LLM APIs (e.g., OpenAI, Azure OpenAI, Anthropic) and familiarity with one orchestration framework (LangChain, LlamaIndex, or similar)
  • Git basics - comfortable with branching and reviewing code as part of a team workflow
  • Experience building or designing semantic layers, knowledge graphs, or context retrieval systems (RAG pipelines); understands embedding models, chunking strategies, and retrieval optimization
  • Ability to reason about data quality, duplication, and freshness - especially critical for training and maintaining embeddings
  • Fetch and ingest data from live external sources (APIs and web sources) into a structured pipeline - handling formats, rate limits, and failures, not just calling a pre-built connector
  • Design and build the schema and storage layer your pipeline writes to, in collaboration with data engineering, comfortable with vector storage or semantic indexing patterns
  • Build and test AI components - embeddings, retrieval logic, prompts - using established patterns and tools; iterate on context relevance and accuracy

Communication & Collaboration
  • Communicates technology-related updates and requirements to other departments and contributes to presentations for senior management.
  • Collaborates with research and development teams, product management, and strategic analysts to support ongoing projects.

Leadership & Management
  • Partners with Business Units to provide reliable intelligence, validated technology options, and insights on enterprise and industry trends.
  • Supports technology project teams by coordinating specific tasks, assisting with day-to-day operations, and contributing to the successful delivery of solutions.
  • Assists in collaborative efforts with academic research teams, practicums, internships, and vendor POCs.

External Relationships & Partnerships
  • Supports vendor evaluations and contributes to collaborations with vendors.
  • Assists as a liaison between academic institutions, professional organizations, and research groups as needed.

Other
  • Support the Academic Corporate Engagement efforts to develop research and educational talent, with a focus on enhancing health tech knowledge and skills.
  • Complete all responsibilities and goals outlined in the internship program.
  • Complete all special projects and other duties as assigned.
  • Must be able to perform duties with or without reasonable accommodation.

This job description is intended to describe the general nature and level of work being performed in this internship. It is not an exhaustive list of responsibilities, duties, and skills required and does not constitute an employment agreement. This job description is subject to change as Cotiviti's needs and requirements of the internship evolve.
Qualifications
  • Currently pursuing or recently completed an advanced degree in healthcare, technology, or a related field (e.g., Biomedical Informatics, Computer Science) with preference of a PhD.
  • Demonstrated interest or experience in AI, healthcare technology, or informatics research.
  • Strong foundational knowledge in generative AI model development, architectures, and vector databases.
  • Hands-on experience with working with Machine Learning and Deep Learning models. Experience with LLM/RAG models and LLM fine-tuning is a plus.
  • Hands-on experience working with cloud services (AWS/Azure), large data sets, and building data pipelines for ML solutions. Experience with vector embeddings and databases is a plus.
  • Ability to work collaboratively and communicate effectively with cross-functional teams.

Mental Requirements:
  • Communicating with others to exchange information.
  • Assessing the accuracy, neatness, and thoroughness of the work assigned.

Physical Requirements and Working Conditions:
  • Remaining in a stationary position, often standing or sitting for prolonged periods.
  • Repeating motions that may include the wrists, hands, and/or fingers.
  • Must be able to provide a dedicated, secure work area.
  • Must be able to provide high-speed internet access/connectivity and office setup and maintenance.
  • No adverse environmental conditions are expected.

Base compensation ranges from $32.00 to $40.00 per hour. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs.
Nonexempt employees are eligible to receive overtime pay for hours worked in excess of 40 hours in a given week, or as otherwise required by applicable state law.
Date of posting: 6/18/2026
Applications are assessed on a rolling basis. We anticipate that the application window will close on 7/18/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.
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