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Trainee Large Language Model Llm Jobs (NOW HIRING)

LLM Specialist

Columbia, MD · On-site

$104K - $145K/yr

The LLM Specialist will drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem. This role leads innovation ...

LLM Specialist

Columbia, MD · On-site +1

$104K - $145K/yr

The LLM Specialist will drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem. This role leads innovation ...

LLM Engineer About the role As LLM Engineer , you will make an impact by designing, building, optimizing, and deploying Large Language Model (LLM) and Small Language Model (SLM) solutions that power ...

Systems Architect

Las Vegas, NV · On-site

$232K/yr

... Large Language Model LLM Architecture Prompt Engineering Agentic AI Frameworks Banking Domain Accounting Domain Financial Automation Technology Leadership Negotiation Skills Program Delivery Project ...

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Trainee Large Language Model Llm information

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

As of Sep 13, 2026, the average hourly pay for trainee large language model llm in the United States is $21.15, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $24.28 per hour, depending on experience, location, and employer.

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

AspectTrainee Large Language Model LlmData Scientist
Required CredentialsTypically pursuing or recent graduate in computer science, AI, or related fieldsBachelor's or master's in data science, statistics, computer science
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness analytics, research, product development teams
Industry UsageAI research, NLP projects, machine learning developmentData analysis, predictive modeling, decision support

While both roles involve working with data and algorithms, a Trainee Large Language Model Llm focuses on developing and training language models, often in research or AI labs. A Data Scientist applies statistical and analytical skills to interpret data and support business decisions. The roles differ mainly in their focus—AI model training versus data analysis—though they share foundational skills in programming and data handling.

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Infographic showing various Trainee Large Language Model Llm job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $43,990 per year, or $21.1 per hour.

LLM Engineer (GCP Preferred)

Atlanta, GA • Hybrid

$58 - $60/hr

Contractor

Re-posted 18 days ago


Job description

Job Title: LLM Engineer (GCP Preferred)

Work Time Zone: EST

Rate: $60/hour on 1099/C2C

Location: Atlanta, GA (Hybrid – 3 days on-site)

 

We are seeking a highly skilled and motivated LLM Engineer to design, build, and deploy advanced large language model (LLM) solutions that enhance procurement workflows and drive business automation. The ideal candidate will have a strong background in natural language processing, deep learning, and AI agent design, with hands-on experience fine-tuning foundation models and deploying them on Google Cloud Platform (GCP).


Key Responsibilities:

  • AI Agent Development
    Design and implement LLM-powered AI agents that optimize and automate procurement-related tasks, ensuring reliability, explainability, and business alignment.
  • Model Fine-Tuning & Optimization
    Fine-tune foundation models for domain-specific tasks, focusing on accuracy, latency, and scalability. Apply techniques such as parameter-efficient fine-tuning, prompt tuning, and adapter training.
  • Pipeline Engineering
    Build and maintain robust, production-grade pipelines for data ingestion, model training, evaluation, and inference using GCP services and open-source tools.
  • Prompt Engineering & RAG Implementation
    Leverage prompt engineering and Retrieval-Augmented Generation (RAG) to improve contextual accuracy and relevance of model outputs.
  • Stakeholder Collaboration
    Work closely with procurement experts, data engineers, and business leaders to gather requirements, align goals, and deliver impactful AI solutions.
  • Model Evaluation & Monitoring
    Establish evaluation metrics and monitoring tools to track model performance, accuracy, bias, and drift in real-world applications.
  • Integration & Deployment
    Collaborate with cross-functional teams to integrate LLMs into existing systems, leveraging LangChain, LangGraph, and GCP AI tools like Vertex AI for seamless deployment.

Must-Have Qualifications:

  • Master’s degree in mathematics, Physics, Computer Science,
  • 7 – 10 + years of experience in NLP, LLM development, or AI-driven automation.
  • Expertise in Python and deep learning frameworks such as PyTorch and TensorFlow.
  • Proficiency with LangChain, LangGraph, Hugging Face Transformers, and LLM model hubs.
  • Experience fine-tuning large-scale models and optimizing for real-time inference.
  • Solid understanding of vector databases, knowledge graphs, and embedding techniques.
  • Strong communication skills with the ability to translate complex AI concepts to non-technical stakeholders.
  • Proven experience working with Google Cloud Platform (GCP), especially with services like Vertex AI, BigQuery, and Cloud Functions.
  • Familiarity with multi-agent systems and reinforcement learning is a strong plus.