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Hourly Large Language Model Llm Jobs (NOW HIRING)

Omni Inclusive

AI/ML Expert

Plano, TX

NLP (Natural Language Processing) Generative AI & Large Language Models (LLM) Python Skills Educational Qualifications: Graduate or Doctorate degree in information technology, Neuroscience, Business ...

My3Tech Inc

Data Engineer

Cincinnati, OH

$109K - $132K/yr

RAG Type LLM Workflows: * Develop and maintain data pipelines specifically tailored for Retrieval-Augmented Generation (RAG) type Large Language Model (LLM) workflows. * Ensure efficient data ...

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Hourly Large Language Model Llm information

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

As of Jun 9, 2026, the average hourly pay for hourly large language model llm in the United States is $24.34, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $29.09 per hour, depending on experience, location, and employer.

What is the difference between Hourly Large Language Model Llm vs Data Scientist?

AspectHourly Large Language Model LlmData Scientist
Required CredentialsKnowledge of AI, NLP, programming skillsDegree in Data Science, Statistics, or related field
Work EnvironmentTech companies, AI research labs, freelance projectsCorporate, consulting firms, research institutions
Industry UsageDeveloping and fine-tuning language models, AI applicationsData analysis, predictive modeling, data visualization

While both roles involve working with data and advanced technology, Hourly Large Language Model Llm focuses on developing and deploying AI language models, whereas Data Scientists analyze data to inform business decisions. The roles share skills in programming and data handling but differ in their primary objectives and work environments.

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

To thrive as a Large Language Model (LLM) Engineer, you need a solid background in machine learning, natural language processing, and programming—typically with a degree in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, familiarity with cloud platforms, and knowledge of model deployment tools are highly valued, along with certifications in AI or data science. Strong problem-solving skills, creativity, and effective communication help you collaborate with cross-functional teams and innovate solutions. These competencies are crucial for developing, optimizing, and scaling LLMs to meet evolving business and research needs.

What are some common challenges faced by Hourly Large Language Model (LLM) annotators and how can they be addressed?

Hourly LLM annotators often face challenges such as maintaining consistency in labeling, handling ambiguous or unclear data, and managing the repetitive nature of annotation tasks. To address these challenges, it's helpful to regularly review annotation guidelines, participate in team discussions to clarify uncertainties, and leverage available feedback from quality assurance checks. Collaborating with teammates and project managers can also provide support and ensure alignment on task expectations, making the work environment more collaborative and improving overall accuracy.

What are Hourly Large Language Model (LLM) jobs?

Hourly Large Language Model (LLM) jobs are roles where individuals work with LLMs, such as ChatGPT or similar AI systems, on an hourly basis. These positions often involve tasks like data annotation, prompt engineering, AI model evaluation, or content generation. Workers may be responsible for improving AI responses, testing models, or creating training data. The 'hourly' aspect means they are paid based on the number of hours worked, rather than a fixed salary or per-project rate. Such jobs are common in tech companies, research organizations, or freelance platforms.
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Hourly Large Language Model Llm jobs near you
Infographic showing various Hourly Large Language Model Llm job openings in the United States as of May 2026, with employment types broken down into 18% Internship, 64% Full Time, and 18% Contract. Highlights an 91% In-person, and 9% Hybrid job distribution, with an average salary of $50,625 per year, or $24.3 per hour.

GenAI Engineer - Azure OpenAI & AWS Bedrock

Prophecy Technologies

Malvern, PA • On-site

$126K/yr

Full-time

Posted 25 days ago

Job description

Job Summary:
We are seeking a GenAI Engineer with hands-on experience in Azure OpenAI and AWS Bedrock to design, develop, and deploy scalable Generative AI solutions. The role focuses on building Retrieval-Augmented Generation (RAG) pipelines, integrating Large Language Models (LLMs) into enterprise applications, and ensuring performance, security, and cost efficiency in AI-driven systems.
Location:
Malvern, PA - Onsite
Key Responsibilities:
  • Design, develop, and implement Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, chunking, and embedding generation.
  • Configure, manage, and optimize vector databases for semantic and hybrid search performance.
  • Securely integrate Large Language Model (LLM) APIs into enterprise applications and workflows.
  • Develop and manage prompt templates and context-handling strategies to ensure consistent and accurate LLM responses.
  • Implement monitoring and logging for LLM usage, performance, latency, and cost tracking.
  • Build reusable AI components, frameworks, and SDKs to enable AI integration across multiple business use cases.

Required Skills & Experience:
  • Strong hands-on experience with Azure OpenAI services.
  • Experience working with AWS Bedrock and related AWS AI services.
  • Proficiency in Python for AI/ML and backend development.
  • Experience designing and deploying RAG architectures.
  • Knowledge of vector databases and embedding-based search solutions.
  • Experience integrating LLM APIs into applications securely.

Competencies:
  • Strong analytical and problem-solving skills.
  • Ability to design scalable and reusable AI solutions.
  • Attention to performance, security, and cost optimization.
  • Strong communication skills and ability to collaborate with cross-functional teams.

Preferred Skills:
  • Experience with hybrid cloud AI architectures (Azure + AWS).
  • Familiarity with MLOps, observability, and cost-governance practices for GenAI solutions.
  • Experience building AI SDKs or shared AI platforms.

Apply