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Internship Large Language Model Llm Jobs in Colorado

Senior Applied AI/ML Scientist

Denver, CO · On-site

$180K - $225K/yr

We want people who like working in a collaborative team environment and enjoy creating practical, efficient, and high-performance software that leverages Large Language Models (LLM), Multimodal ...

Design semantic models and data products with AI-readiness in mind-ensuring metadata quality, field descriptions, and schema consistency support large language model (LLM) integrations * Collaborate ...

... and Large Language Models (LLMs). This role involves modern functional quality engineering to ... Evaluate LLM responses for accuracy, relevance, and consistency. * Test prompt engineering ...

Leverage large language model (LLM) orchestration patterns including ReAct, chain-of-thought prompting, and tool-calling to build reliable, goal-directed agents. * Prototype and iterate rapidly on ...

We are looking for highly skilled AI Engineers with expertise in Large Language Models (LLMs) and ... Solid understanding of LLM architectures, embeddings, and retrieval-augmented generation (RAG)

AI Solutions Analyst

Greeley, CO · On-site

$90K - $127K/yr

Leverage large language model (LLM) orchestration patterns including ReAct, chain-of-thought prompting, and tool-calling to build reliable, goal-directed agents. * Prototype and iterate rapidly on ...

LLM Ops Engineer

Denver, CO · Hybrid

$105K - $130K/yr

As an LLM Ops Engineer, you will create the secure, scalable, and reliable foundation that allows ... Experience fine-tuning or training large language models for domain-specific applications.

LLM Ops Engineer

Denver, CO · On-site

$105K - $130K/yr

As an LLM Ops Engineer, you will create the secure, scalable, and reliable foundation that allows ... Experience fine-tuning or training large language models for domain-specific applications.

... Large Language Models • Google Gemini models • PaLM models • Enterprise LLM integration patterns Google Cloud AI & Platform Expertise • Vertex AI (Gemini/PaLM) • Vertex AI Agent Builder • ...

Proficiency integrating external tools for use with Large Language Model (LLM) agents and the MCP protocol Qualifications: * Education: Bachelor's degree in Computer Science, Applied Mathematics, or ...

Proficiency integrating external tools for use with Large Language Model (LLM) agents and the MCP protocol Qualifications: * Education: Bachelor's degree in Computer Science, Applied Mathematics, or ...

AI Software Engineer

Fort Collins, CO · On-site

$108 - $172.80/hr

Proficiency integrating external tools for use with Large Language Model (LLM) agents and the MCP protocol Qualifications * Education: Bachelor's degree in Computer Science, Applied Mathematics, or a ...

... other large language model (LLM) tools. * Conduct keyword research and implement best practices to increase organic traffic, discoverability, and authoritative brand presence. * Develop content ...

Showing results 21-40

Internship Large Language Model Llm information

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?

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.

What are the most commonly searched types of Large Language Model Llm jobs in Colorado? The most popular types of Large Language Model Llm jobs in Colorado are:
What are popular job titles related to Internship Large Language Model Llm jobs in Colorado? For Internship Large Language Model Llm jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Internship Large Language Model Llm jobs in Colorado look for? The top searched job categories for Internship Large Language Model Llm jobs in Colorado are:

Graduate Intern - LLM Reliability and Uncertainty for AI Science Assistants

The National Renewable Energy Laboratory (NREL)

Golden, CO • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 23 days ago


Job description

Posting Title
Graduate Intern - LLM Reliability and Uncertainty for AI Science Assistants
Location
CO - Golden
Position Type
Intern (Fixed Term)
Hours Per Week
40
Working at NLR
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.
Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.
At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.
Job Description
The AI, Learning and Intelligent Systems group in the NLR Computational Science Center has an opening for a graduate student researcher in LLM Reliability and Uncertainty for AI Science Assistants. The researcher will investigate methods for quantifying uncertainty in LLM-based science assistants over multi-turn scientific dialogue, with an emphasis on flagging when a scientific question or task is underspecified or ill-posed. In practice, scientific questions can be vague, open-ended, or underdetermined. LLM-based assistants can quietly insert their own assumptions into such requests to fill the gap instead of raising concerns to their human counterpart. This internship will investigate if the assistant's internal representations can be probed to detect these instances so they may be flagged for the user or used to trigger clarifying questions. We are looking for a dynamic, motivated researcher with a strong technical background and an interest in AI for science, uncertainty-aware machine learning, human-AI scientific workflows, and trustworthy AI. The successful candidate must be able to work at the intersection of machine learning research and practical AI system integration.
Responsibilities include:
  • Research and evaluate uncertainty quantification and hallucination detection methods for multi-turn, agentic scientific workflows
  • Develop probing methods that predict, from a model's internal representations, when a scientific task specification is incomplete or inconsistent and a clarifying question is warranted
  • Build and instrument evaluation pipelines that capture and analyze model internal states over multi-turn scientific dialogue on HPC systems
  • Conduct experiments and analyze model behavior across computational science domains and established benchmarks
  • Contribute to technical documentation, research reports, publications, and presentations summarizing project progress and findings
  • Develop, test, and maintain high-quality research code and evaluation pipelines

Basic Qualifications
Minimum of a 3.0 cumulative grade point average.
Undergraduate: Must be enrolled as a full-time student in a bachelor's degree program from an accredited institution.
Post Undergraduate: Earned a bachelor's degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate: Must be enrolled as a full-time student in a master's degree program from an accredited institution.
Post Graduate: Earned a master's degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master's degree and enrolled as PhD student from an accredited institution.
Please Note:
• Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process.
• If selected for position, a letter of recommendation will be required as part of the hiring process.
• Must meet educational requirements prior to employment start date.
* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
  • Familiarity with large language models, including agentic, tool-using, or multi-turn conversational LLM systems
  • Experience developing or evaluating machine learning models for classification, uncertainty estimation, or related tasks
  • Knowledge of probabilistic machine learning or uncertainty quantification concepts
  • Hands-on experience with open-weight LLMs and modern deep learning frameworks
  • Experience running Python code on HPC or multi-GPU systems
  • Strong software engineering and debugging skills
  • Ability to work independently while collaborating effectively in a multidisciplinary research environment

Preferred Qualifications
  • Research experience related to hallucination detection, uncertainty quantification, interpretability, explainability, or trustworthy AI
  • Familiarity with representation probing or mechanistic interpretability methods
  • Experience with LLM benchmarking and evaluation, including multi-turn or conversational agent evaluation and LLM-as-a-judge protocols
  • Experience with scientific question-answering systems, AI for science applications, or scientific agent frameworks
  • Coursework or research background in a computational science domain (e.g., fluid mechanics, solid mechanics, materials science, or numerical methods for PDEs)

Job Application Submission Window
The anticipated closing window for application submission is up to 30 days and may be extended as needed.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: / Annual Salary Range: $44,500 - $71,200
NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.
Benefits Summary
Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.
* Based on eligibility rules
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement.
Drug Free Workplace
NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
Submission Guidelines
Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
Reasonable Accommodations
E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish.
E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.