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Large Language Model Llm Jobs in Georgia (NOW HIRING)

Georgia Transmission

Data Scientist (AI/ML)

Tucker, GA · On-site

In addition to traditional machine learning techniques, the role contributes to the organization's AI strategy through the development and implementation of Large Language Model (LLM) solutions ...

Optimal Inc.

Agentic AI Engineer

Embry Hills, GA

... ML, LLM development, or agent-based systems * Strong hands-on experience with large language models (prompt engineering, fine-tuning, evaluation) * Experience building or working with agent ...

Saicon Consultants Inc.

Engineering Lead

Milton, GA · On-site

$97K - $128K/yr

Hands-on experience working with Large Language Models (LLM) and Generative AI (GenAI) technologies. * Oversee the use and management of Azure infrastructure, GitHub repositories, and GitHub Actions ...

Candescent

Principal AI Security Engineer

Atlanta, GA · On-site

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.

Infosys

Principal - AI Architect - Insurance

Atlanta, GA · On-site

$154K - $193K/yr

Generative AI and Large Language Model (LLM) based solutions * Predictive and prescriptive Machine Learning models * Computer Vision * Natural Language Processing (NLP) and Conversational AI

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Large Language Model Llm information

What are some common challenges faced by Large Language Model (LLM) Engineers in their day-to-day work?

LLM Engineers often encounter challenges related to scaling models efficiently, optimizing performance on large and complex datasets, and ensuring the responsible use of AI technologies. Balancing the trade-offs between model accuracy, speed, and ethical considerations can be demanding, especially as real-world applications often require rapid iterations and rigorous testing. Additionally, staying updated with the latest research advancements and integrating new methods into production systems is an ongoing responsibility. Many engineers tackle these challenges by working closely with data scientists, researchers, and product teams in collaborative, agile environments.

What is a Large Language Model (LLM) job?

A Large Language Model (LLM) job typically involves working with advanced AI models designed to understand and generate human-like text. Roles in this field may include research, data engineering, model fine-tuning, prompt engineering, or application development. Professionals in LLM jobs often work with machine learning algorithms, natural language processing (NLP), and large-scale datasets to enhance AI capabilities. These roles are common in AI-driven industries, including tech companies, research institutions, and startups. Strong programming skills, knowledge of deep learning frameworks, and expertise in NLP are often required.

Which 3 jobs will survive AI?

Large Language Model (LLM) specialists, healthcare professionals, and skilled tradespeople are likely to continue thriving as AI automates routine tasks. These roles require complex decision-making, emotional intelligence, or manual skills that are difficult for AI to replicate fully. Continuous learning and adaptability remain important for job security in these fields.

What jobs can I do with LLM?

Large Language Models (LLMs) are used in roles such as AI research scientist, NLP engineer, data scientist, and machine learning engineer. These jobs involve developing, fine-tuning, and deploying LLMs, often requiring skills in programming, data analysis, and understanding of AI frameworks like TensorFlow or PyTorch.

What are the key skills and qualifications needed to thrive in the Large Language Model Llm position, and why are they important?

Excelling in the role of a Large Language Model (LLM) Engineer requires strong expertise in natural language processing, machine learning, and computer programming, often supported by an advanced degree in computer science or a related field. Familiarity with industry-standard frameworks like PyTorch or TensorFlow, as well as experience with cloud computing platforms and large-scale data management, is highly valued. Communication, creativity, and problem-solving are essential soft skills to effectively collaborate with cross-functional teams and innovate solutions. These skills ensure the development, deployment, and refinement of powerful language models that can address diverse business needs and technical challenges.

What jobs pay 500,000 a year?

High-paying jobs that can reach or exceed $500,000 annually include executive roles such as CEOs, CFOs, and other C-suite positions, as well as specialized professions like top-tier surgeons, investment bankers, and successful entrepreneurs. These roles typically require extensive experience, advanced skills, and often involve leadership, risk management, or highly specialized expertise.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level positions in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms. Compensation at this level reflects significant expertise and responsibility in developing and deploying AI systems.
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Large Language Model Llm jobs near you
Infographic showing various Large Language Model Llm job openings in Georgia as of July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 22% Part Time, 1% Temporary, and 4% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution.

LLM Engineer (GCP Preferred)

Krest Global Solutions

Atlanta, GA • Hybrid

$58 - $60/hr

Contractor

Posted 11 hours 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.