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Llm Developer Jobs in Dallas, GA (NOW HIRING)

Prolego

GenAI Systems Developer

Atlanta, GA · Remote

$185K - $215K/yr

Prolego is seeking Gen AI Systems Developers to design, build, and customize cutting-edge AI ... Develop custom methods to test and validate LLM performance. * Interfaces & Integrations: Create ...

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

$120 - $165/hr

Work hands‑on with multiple LLM ecosystems: * OpenAI GPT models (GPT‑4, GPT‑4o, fine‑tuned ... Conduct feature engineering, preprocessing, and embeddings generation for structured and ...

Digipulse Technologies, Inc

AI Engineer

Atlanta, GA · On-site

$69K - $89K/yr

Azure DevOps, Git, and Azure OpenAI * Arize AI or similar observability tools Responsibilities * Design and execute test plans for GenAI and LLM applications * Test prompts, agents, APIs ...

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Llm Developer information

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$23

$45

$71

How much do llm developer jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for llm developer in Dallas, GA is $45.32, according to ZipRecruiter salary data. Most workers in this role earn between $35.62 and $54.95 per hour, depending on experience, location, and employer.

What does an LLM Developer do?

An LLM Developer designs, fine-tunes, and implements large language models (LLMs) for various applications, such as chatbots, content generation, and AI-driven tools. They work with machine learning frameworks, optimize model performance, and ensure efficient deployment. This role requires expertise in natural language processing (NLP), deep learning, and programming languages like Python.

What are the key skills and qualifications needed to thrive as an LLM Developer?

To excel as an LLM Developer, you need strong expertise in natural language processing (NLP), deep learning frameworks, and programming languages such as Python, typically supported by a degree in computer science or a related field. Familiarity with machine learning libraries (like TensorFlow or PyTorch), cloud computing platforms, and experience with prompt engineering or fine-tuning large language models is crucial. Excellent problem-solving abilities, collaboration, and effective communication skills help you design solutions and work efficiently within multidisciplinary teams. These qualifications are essential for successfully building, deploying, and optimizing large language models that drive impactful AI applications.

What is the role of a Llm developer?

A Large Language Model (LLM) developer designs, trains, and fine-tunes large-scale AI models for natural language processing tasks. They work with machine learning frameworks, handle large datasets, and optimize models for performance and accuracy, often requiring knowledge of programming languages like Python and tools such as TensorFlow or PyTorch.
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What cities near Dallas, GA are hiring for Llm Developer jobs? Cities near Dallas, GA with the most Llm Developer job openings:
Llm Developer jobs near you
Infographic showing various Llm Developer job openings in Dallas, GA as of July 2026, with employment types broken down into 82% Full Time, 8% Part Time, and 10% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $94,267 per year, or $45.3 per hour.

LLM Engineer (GCP Preferred)

Krest Global Solutions

Atlanta, GA • Hybrid

$58 - $60/hr

Contractor

Re-posted 15 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.