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Commission Large Language Model Llm Jobs in Georgia

AI Architect

Atlanta, GA · On-site

$60.50 - $79.75/hr

Build and deploy Generative AI, NLP, and Large Language Model (LLM) solutions for healthcare workflows. * Design data pipelines for structured and unstructured healthcare data. * Integrate AI ...

Role Summary We are seeking an AI Security Engineer to own the security of how we adopt and integrate third-party artificial intelligence and large language model (LLM) services across the enterprise.

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Commission Large Language Model Llm information

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

AspectCommission Large Language Model LlmData Scientist
Required credentialsAdvanced degrees in AI, NLP, or related fields; experience with machine learningDegree in Data Science, Statistics, Computer Science, or related fields; strong analytical skills
Work environmentResearch labs, AI companies, tech firms focusing on NLP and AI developmentCorporate, research institutions, or tech companies analyzing data and building models
Industry usageAI development, NLP applications, language modeling projectsData analysis, predictive modeling, business insights across industries

While both roles require expertise in data and machine learning, Commission Large Language Model Llm focuses on developing and fine-tuning language models, whereas Data Scientists analyze data to generate insights and build predictive models. The roles often overlap in skills but differ in primary responsibilities and work environments.

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Cities in Georgia with the most Commission Large Language Model Llm job openings:

LLM Engineer (GCP Preferred)

Krest Global Solutions

Atlanta, GA • Hybrid

$58 - $60/hr

Contractor

Re-posted 20 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.