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Volunteer Large Language Model Llm Jobs (NOW HIRING)

CACI International Inc.

Deploy LLM solutions across cloud-based and local resources using kubernetes (llama.ccp, vllm etc ... Large Language Models and experience identifying ways to incorporate them into new areas and ...

Source Infotech

Gen AI Engineer

Charlotte, NC · On-site

Large Language Model (LLM) & Retrieval-Augmented Generation (RAG): * Develop and fine-tune large language models like GPT, Gemini, Langchain, and Llama for specific business needs. * Implement RAG ...

New

Xforia, Inc.

Data Scientist

... Large Language Model (LLM) solution to check coherence and consistency. Resource will also develop and modify existing models related to customer long term engagement and retention. This role will ...

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

As of Sep 14, 2026, the average hourly pay for volunteer large language model llm in the United States is $19.14, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $20.19 per hour, depending on experience, location, and employer.

What is a volunteer large language model LLM?

Volunteer Large Language Model (LLM) roles involve individuals contributing their time and expertise to support the development, testing, or improvement of large language models. Volunteers may help by annotating data, testing models for biases, providing feedback, or assisting with community moderation and outreach. This work is important for advancing the accuracy, fairness, and usefulness of language models, and often takes place within open-source or academic projects. Volunteers typically do not receive monetary compensation but gain experience and contribute to impactful technology.

What skills and qualifications are needed to thrive as a volunteer large language model LLM?

To thrive as a Volunteer Large Language Model LLM, you need a deep understanding of natural language processing, machine learning principles, and strong programming skills, typically supported by education in computer science or related fields. Familiarity with frameworks like TensorFlow or PyTorch, experience with large-scale data sets, and knowledge of cloud platforms are commonly required. Adaptability, collaboration, and effective communication are important soft skills for working in open-source or community-driven AI projects. These skills are crucial to developing, refining, and responsibly deploying advanced language models in dynamic and collaborative environments.

What are common challenges faced by volunteer large language model LLM contributors, and how can they be addressed?

Volunteer LLM contributors often encounter challenges such as coordinating with a distributed team, managing their time effectively alongside other commitments, and staying updated on rapidly evolving AI technologies. Collaboration tools like shared code repositories and communication platforms help streamline teamwork and reduce miscommunication. To address these challenges, it's helpful to set clear expectations, regularly participate in team meetings, and proactively seek feedback from experienced contributors. This approach not only fosters a supportive environment but also enhances your learning experience and impact.

What is the difference between Volunteer Large Language Model Llm vs Data Annotator?

AspectVolunteer Large Language Model LlmData Annotator
Required credentialsNone or basic technical knowledgeBasic computer skills, sometimes specific software training
Work environmentRemote or online, collaborativeOffice or remote, task-specific
Industry usageAI development, NLP projectsData labeling, machine learning training
Common search intentUnderstanding AI model training rolesData labeling and annotation roles

Volunteer Large Language Models (LLMs) are involved in training and improving AI language models, often through collaborative, volunteer efforts. Data Annotators focus on labeling data to train machine learning models. While both roles support AI development, LLM volunteers typically contribute to model training directly, whereas Data Annotators prepare data for such training.

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Volunteer Large Language Model Llm jobs near you
Infographic showing various Volunteer Large Language Model Llm job openings in the United States as of September 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $39,804 per year, or $19.1 per hour.

Principal AI/ML Engineer (Large Language Model) Aurora, CO, US + 1 more

On-site

CACI International Inc.
See more jobs at CACI International Inc.external

Other

Medical, Retirement, PTO

Posted 15 days ago

Key responsibilities

  • Lead and mentor a multidisciplinary team to implement machine learning algorithms for various challenges.

  • Apply Large Language Models (LLMs) to applications such as tasking collections, identifying gaps, and analyzing patterns of life.

  • Build, fine-tune, and deploy LLM solutions using frameworks, cloud resources, and techniques like retrieval augmented generation.

Job description

Job Title: Principal AI/ML Engineer (Large Language Model)

Job Category: Science

Time Type: Full time

Minimum Clearance Required to Start: TS/SCI with Polygraph

Employee Type: Regular

Percentage of Travel Required: Up to 10%

Type of Travel: Local

Anticipated Posting End: 12/31/2026

The Opportunity

The Principal AI/ML Engineer will support the development of AI/ML algorithms in a multitude of disciplines from object detection/classification, natural language processing, reinforcement learning, and large language models.

Responsibilities
  • Lead and mentor a multidisciplined team consisting of developers and researchers to implement machine learning algorithms to solve a broad set of challenges for our various customers
  • Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as tasking collections, identifying gaps in collection plans, analyzing patterns of life, and more.
  • Fine tune foundation models and building adaptors for new applications (llama factory, PEFT)
  • Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate)
  • Build custom applications with LLM frameworks such as LangChain, DSPy
  • Deploy LLM solutions across cloud-based and local resources using kubernetes (llama.ccp, vllm etc)
  • Analyze large multi-domain datasets such as images, text and/or graph data, to identify statistically relevant features to build models that provide analysts with actionable data
  • Review relevant publications to understand and apply cutting edge concepts to defense and commercial applications
  • Interface with both internal and external leadership to communicate technical status
QualificationsRequired
  • Active TS/SCI with Adjudicated Polygraph
  • BS in machine learning, computer science, mathematics, or related fields.
  • 10+ years of experience, preferably in software development or as a data scientist with 2+ years of building LLM applications using some of the following:
    • Fine-tuning foundational models
      • Steering Techniques (e Sparse auto encoders, representation tuning)
      • Building adapters to use foundational models (e.g. PEFT, llama factory)
    • Prompt engineering techniques / Inference time techniques (e.g. chain of thought, tree of thoughts, etc.)
    • Using Retrieval Augmented Generation techniques to populate and query vector databases (e.g. Weaviate, pinecone)
    • Using LLM Frameworks (e.g. LangChain, DSPy)
    • Using AI APIs ( e.g AWS Bedrock, OpenAI)
    • Using LLM deployment frameworks (eg llama.cpp, vllm, tgi)
    • Developing UIs with ReAct
    • Experience leading an interdisciplinary team of researchers and software developers and working with a program manager to define project scope and schedule to ensure we meet project milestones as defined by our customers
    • Experience with Python and data science / machine learning libraries (e.g. PyTorch, TensorFlow, Keras, OpenCV, NumPy, Pandas, Polars, scikit-learn, etc.)
Desired
  • MS or PhD in machine learning, computer science, mathematics, or related fields.
  • Experience leading an interdisciplinary team of researchers and software developers
  • Experience with any of the following Computer Vision domains:
    • Large Language Models and experience identifying ways to incorporate them into new areas and applications
    • Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision
    • Object detection algorithms such as YOLO and Faster-RCNN
    • Natural Language Processing algorithms such as BERT
    • Generative Adversarial Networks and Variational Autoencoders
    • Reinforcement learning and familiarity with Gymnasium Gym, RLlib, and Stable Baselines
    • Applying clustering algorithms and/or deep neural networks to real life problems
    • Implementing tracking and pattern-of-life algorithms
  • Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
  • Experience with Computer Vision libraries such as OpenCV, Nerfstudio, FiftyOne, etc.
  • Experience with Linux
  • Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda, etc.
  • Experience with any of the following additional languages: Java, C++, Rust, Go, and/or C#
  • Experience implementing algorithms on the GPU in Python or C++ using CUDA and other CUDA libraries
  • Experience implementing tracking and pattern-of-life algorithms
  • Experience in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher)
  • Experience working with various Remote Sensing datasets (e.g. EO/OPIR/SAR images, passive RF, etc.)
  • Experience shaping and writing proposals
What You Can Expect

A culture of integrity.

At CACI, we place character and innovation at the center of everything we do. As a valued team member, you’ll be part of a high-performing group dedicated to our customer’s missions and driven by a higher purpose – to ensure the safety of our nation.

An environment of trust.

CAC I values the unique contributions that every employee brings to our company and our customers - every day. You’ll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality.

A focus on continuous growth.

Together, we will advance our nation's most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground — in your career and in our legacy.

Pay Range

There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.

Since this position can be worked in more than one location, the range shown is the national average for the position.

The proposed salary range for this position is:

$114,600-$252,100

CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any other protected characteristic.

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