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Llm Ml Rag Jobs in Raleigh, NC (NOW HIRING)

CCube Solutions

AI/ML Tech Lead

Raleigh, NC · On-site

$150K - $200K/yr

Position:- AI/ML Tech Lead Location: Raleigh, NC (Hybrid) Job Type: Full Time/W2 Only Exp Level- 8 ... LLM understanding, RAG. Architecture end to end, built systems. We are seeking a highly skilled AI ...

Ccube

AI & ML Tech Lead/Architect

Durham, NC · On-site

$150K - $225K/yr

Position:- AI & ML Tech Lead Location: Raleigh, NC (Hybrid) Job Type: Full Time/W2 Only Exp Level ... LLM understanding, RAG. Architecture end to end, built systems. We are seeking a highly skilled AI ...

Jaggaer

Architect, Data AI

Durham, NC

$61.50 - $79.25/hr

... ML techniques: regression, classification, clustering, time-series forecasting, and predictive modeling. Proven track record of developing and deploying Generative AI, LLM-based, RAG-based, and ...

Jaggaer

Architect, Data AI

Durham, NC · On-site

$61.50 - $79.25/hr

... ML techniques: regression, classification, clustering, time-series forecasting, and predictive modeling. • Proven track record of developing and deploying Generative AI, LLM-based, RAG-based, and ...

Jaggaer

Architect, Data AI

Durham, NC · On-site

$61.50 - $79.25/hr

... ML techniques: regression, classification, clustering, time-series forecasting, and predictive modeling. • Proven track record of developing and deploying Generative AI, LLM-based, RAG-based, and ...

RIT Solutions, Inc.

Sr Machine Learning Engineer

Raleigh, NC · On-site

$101K - $139K/yr

The role involves deploying LLM/GenAI/RAG systems and requires expertise in cloud technologies and orchestration tools. Qualifications : Required : • 10+ yrs production ML at scale • LLM/GenAI ...

Deloitte

AI Data Engineer - Senior Consultant

Raleigh, NC · Hybrid

$101K - $139K/yr

... science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI ... Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector ...

Deloitte

AI Engineer Senior Consultant

Raleigh, NC · Hybrid

$101K - $139K/yr

... science/ML, security, and platform engineering to deliver reliable, secure, and scalable AI ... Implement LLM application patterns including RAG, document ingestion/chunking, embeddings, vector ...

Deloitte

AI Engineer Consultant

Raleigh, NC · Hybrid

... ML and LLM-based experiences. Key Responsibilities: * Partner with the Lead AI Solutions Architect ... Implement RAG and document intelligence patterns (ingestion, chunking, embeddings, vector/hybrid ...

CVS Health

Staff Software Architect

Raleigh, NC · On-site

Define and govern ML architecture patterns -- including feature stores, model registries, model ... Hands-on experience with LLM-based clinical document processing, RAG architectures, OCR pipelines ...

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All JobsLlm Ml Rag JobsLlm Ml Rag Jobs in Raleigh, NC

Llm Ml Rag information

See Raleigh, NC salary details

$43.7K

$73.2K

$106.9K

How much do llm ml rag jobs pay per year?

As of Jun 27, 2026, the average yearly pay for llm ml rag in Raleigh, NC is $73,197.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,300.00 and $84,600.00 per year, depending on experience, location, and employer.

What are some typical challenges faced when working on Retrieval-Augmented Generation (RAG) systems in large language model (LLM) machine learning roles?

Professionals working on LLM ML RAG systems often encounter challenges such as ensuring the accuracy and relevancy of retrieved documents, managing latency for real-time queries, and seamlessly integrating retrieval mechanisms with generation models. Additionally, keeping up with evolving datasets and maintaining high-quality knowledge bases can be demanding. Collaboration with data engineers and domain experts is common to refine retrieval pipelines and optimize the end-to-end system.

What is the difference between Llm Ml Rag vs Data Scientist?

AspectLlm Ml RagData Scientist
Required CredentialsMaster's or PhD in ML, AI, or related fields; certifications in ML frameworksDegree in Computer Science, Statistics, or related; certifications in data analysis or ML
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness analytics, research, product development teams
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, tech, consulting firms
Common Search & ComparisonOften compared for ML specialization and research focusCompared for data analysis, modeling, and business insights

While both roles involve working with machine learning, Llm Ml Rag typically focuses on research and development of large language models, requiring advanced ML expertise. Data Scientists often work on analyzing data, building predictive models, and deriving insights for business decisions. The roles overlap in skills but differ in focus and application areas.

What are the key skills and qualifications needed to thrive as an LLM ML RAG (Retrieval-Augmented Generation) Engineer, and why are they important?

To excel as an LLM ML RAG Engineer, you need a strong background in machine learning, natural language processing, and large language models, typically supported by a degree in computer science or a related field. Proficiency with tools and frameworks like Python, PyTorch/TensorFlow, Hugging Face Transformers, and vector databases (e.g., FAISS, Pinecone) is essential, along with experience in deploying and fine-tuning LLMs and integrating retrieval systems. Strong problem-solving skills, attention to detail, and the ability to collaborate with cross-functional teams distinguish top performers in this role. These skills ensure the effective development and deployment of advanced AI solutions that combine generative and retrieval capabilities for high-impact applications.

What are LLM ML RAG jobs?

LLM ML RAG jobs involve working with Large Language Models (LLMs), Machine Learning (ML), and Retrieval-Augmented Generation (RAG) systems. Professionals in these roles typically design, develop, and optimize AI systems that combine language models with retrieval techniques to improve accuracy, relevance, and factual grounding in generated outputs. These jobs often require expertise in natural language processing, deep learning, data engineering, and information retrieval. Key responsibilities might include integrating RAG pipelines, fine-tuning LLMs, and ensuring high-quality responses from AI applications.
What are popular job titles related to Llm Ml Rag jobs in Raleigh, NC? For Llm Ml Rag jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Llm Ml Rag jobs in Raleigh, NC look for? The top searched job categories for Llm Ml Rag jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Llm Ml Rag jobs? Cities near Raleigh, NC with the most Llm Ml Rag job openings:
Llm Ml Rag jobs near you

AI/ML Tech Lead

CCube Solutions

Raleigh, NC • On-site

$150K - $200K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Position:- AI/ML Tech Lead
Location: Raleigh, NC (Hybrid)
Job Type: Full Time/W2 Only
Exp Level- 8-10 Years
Required Skills- Claude, Vibe Coding, Data Scientist, MCP (Model Context Protocol), Agentic AI, LLM understanding, RAG. Architecture end to end, built systems.
We are seeking a highly skilled AI/ML Leader with a strong foundation in Python and microservices architecture, who can bridge the gap between traditional backend systems and modern AI/ML platforms. The ideal candidate will have experience or a strong interest in LLM-based frameworks (e.g., LangChain, Agentic AI), and be capable of designing scalable, intelligent solutions that integrate with major AI platforms.
Key Responsibilities:
Architect and design scalable, secure, and high-performance microservices using Python.
Collaborate with AI/ML teams to integrate LLM-based tools and frameworks into enterprise applications.
Understand and work with MCP (Model Context Protoco), A2A (Agent-to-Agent) communication, and LLM orchestration frameworks like LangChain and Agentic AI.
Evaluate and recommend AI platforms and tools for enterprise use cases.
Translate business requirements into technical solutions that leverage both traditional and AI-driven components.
Lead technical discussions with stakeholders, including product managers, data scientists, and platform teams.
Ensure architectural alignment with enterprise standards and best practices.
Required Skills & Experience:
5+ years of experience in backend development with Python.
Proven experience designing and deploying microservices architectures.
Familiarity with AI/ML concepts, especially LLMs, prompt engineering, and AI agents.
Understanding of LangChain, Agentic AI, or similar LLM orchestration frameworks.
Experience integrating with AI platforms (e.g., OpenAI, Azure OpenAI, Anthropic, Hugging Face).
Strong understanding of API design, event-driven systems, and cloud-native architectures.
Excellent communication and stakeholder management skills.
Production-level RAG implementation experience.
Hands-on experience with LLM-based applications or AI agent frameworks.
Exposure to MCP, A2A, or similar AI infrastructure concepts.
Experience with containerization (Docker, Kubernetes) and CI/CD pipelines.
Knowledge of data pipelines and AI model lifecycle management
Nice-to-Have / Big Plus:
  • Experience with MCP, A2A, or similar AI infrastructure concepts
  • Knowledge of data pipelines & AI model lifecycle management
  • Prior experience architecting enterprise AI platforms
Why Join Us?
  • Work on real production AI systems, not just POCs
  • Design next-gen Agentic & LLM-powered architectures
  • High ownership, high impact role
  • Flexible Hybrid / Remote setup
  • Collaborate with strong engineering & AI talent

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