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Llm Ml Rag Jobs in Chicago, IL (NOW HIRING)

Vizient, Inc.

Sr AI/ML Engineer

Chicago, IL

$102.40K - $179K/yr

Design and implement RAG pipelines, embedding strategies, and vector search architectures. Build agentic workflows, prompt strategies, and orchestration patterns for LLM systems. Own AI/ML solutions ...

Vizient, Inc.

Sr AI/ML Engineer

Chicago, IL

$102.40K - $179K/yr

Design and implement RAG pipelines, embedding strategies, and vector search architectures. * Build agentic workflows, prompt strategies, and orchestration patterns for LLM systems. * Own AI/ML ...

Vizient

Sr AI/ML Engineer

Chicago, IL · On-site

$102.40K - $179K/yr

Design and implement RAG pipelines, embedding strategies, and vector search architectures. * Build agentic workflows, prompt strategies, and orchestration patterns for LLM systems. * Own AI/ML ...

Vizient

Sr AI/ML Engineer

Chicago, IL

$102.40K - $179K/yr

Design and implement RAG pipelines, embedding strategies, and vector search architectures. * Build agentic workflows, prompt strategies, and orchestration patterns for LLM systems. * Own AI/ML ...

Tata Consultancy Services

Senior AI ML Engineer

Chicago, IL · On-site

$120K - $140K/yr

Must Have Technical/Functional Skill • Hands on experience building ML/LLM based applications • ... RAG pipelines, embeddings, vector search, and LLM orchestration workflows • Develop agentic ...

Nava Software Solutions

Sr. AI/ML Engineer

Deerfield, IL · Hybrid

$106.30K - $145.90K/yr

LLM/GenAI experience: building, fine-tuning, or prompting models such as GPT-4, LLaMA, Claude, etc ... Familiarity with RAG (Retrieval-Augmented Generation) pipelines and integration into enterprise ...

NAVA Software Solutions

Sr. AI/ML Engineer

Deerfield, IL · On-site

$106.30K - $145.90K/yr

LLM/GenAI experience: building, fine-tuning, or prompting models such as GPT-4, LLaMA, Claude, etc ... Familiarity with RAG (Retrieval-Augmented Generation) pipelines and integration into enterprise ...

Veracity

AI / ML Engineering Senior Advisor

Deerfield, IL · On-site

$138.80K - $139.30K/yr

LLM/GenAI experience: building, fine-tuning, or prompting models such as GPT-4, LLaMA, Claude, etc ... Familiarity with RAG (Retrieval-Augmented Generation) pipelines and integration into enterprise ...

Diverse Lynx

Senior AI ML Engineer

Chicago, IL · On-site

$107.70K - $147.90K/yr

AI/ML Engineer Location: Mason, OH / Plano TX / Atlanta, GA / Cleveland, OH / Indianapolis, IN ... end LLM-powered applications and agentic workflows using Python · Design and implement RAG ...

Cooley LLP

Senior AI/ML Engineer

Chicago, IL

$107.70K - $147.90K/yr

Senior AI/ML Engineer Cooley is seeking a Senior AI/ML Engineer to join the Practice Engineering ... LLM applications with enterprise data sources, APIs, and retrieval systems (RAG) * Hands on ...

Cooley

Senior AI/ML Engineer

Chicago, IL · On-site

$107.70K - $147.90K/yr

Senior AI/ML Engineer Cooley is seeking a Senior AI/ML Engineer to join the Practice Engineering ... LLM applications with enterprise data sources, APIs, and retrieval systems (RAG) * Hands on ...

Cooley LLP

Senior AI/ML Engineer

Chicago, IL · On-site

$107.60K - $147.80K/yr

Senior AI/ML Engineer Cooley is seeking a Senior AI/ML Engineer to join the Practice Engineering ... LLM applications with enterprise data sources, APIs, and retrieval systems (RAG) * Hands on ...

Cooley

Senior AI/ML Engineer

Chicago, IL

$107.60K - $147.80K/yr

Senior AI/ML Engineer Cooley is seeking a Senior AI/ML Engineer to join the Practice Engineering ... LLM applications with enterprise data sources, APIs, and retrieval systems (RAG) * Hands on ...

Cengage

AI/ML Engineer - Higher Ed

Chicago, IL · On-site

Strong proficiency in Python with experience building production ML or LLM systems * Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock) * Experience with RAG architectures ...

Cengage Group

AI/ML Engineer - Higher Ed

Chicago, IL · On-site

Strong proficiency in Python with experience building production ML or LLM systems * Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock) * Experience with RAG architectures ...

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Llm Ml Rag information

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$46.4K

$77.6K

$113.3K

How much do llm ml rag jobs pay per year?

As of May 28, 2026, the average yearly pay for llm ml rag in Chicago, IL is $77,569.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,900.00 and $89,600.00 per year, depending on experience, location, and employer.

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 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 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 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 popular job titles related to Llm Ml Rag jobs in Chicago, IL? For Llm Ml Rag jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Llm Ml Rag jobs in Chicago, IL look for? The top searched job categories for Llm Ml Rag jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Llm Ml Rag jobs? Cities near Chicago, IL with the most Llm Ml Rag job openings:
Llm Ml Rag jobs near you

AI/ML Engineer - LLM & Agentic AI

Purple Drive Technologies

Chicago, IL • On-site

Full-time

Posted 15 days ago

Job description

Overview:
Job Title: AI/ML Engineer - LLM & Agentic AI
Location: Chicago, IL / Remote
Job Type: Full-Time
Job Summary
We are seeking a highly skilled AI/ML Engineer with deep expertise in LLM-based applications, Agentic AI, and scalable AI architecture. The ideal candidate will have strong experience building production-grade AI systems using modern frameworks, vector databases, retrieval pipelines, and MLOps practices.
This role involves end-to-end ownership of AI solution design, orchestration workflows, deployment, monitoring, and optimization.
Required Skills
  • Hands-on experience building:
    • ML/LLM-based applications
    • Agentic AI solutions
    • RAG architectures
  • Strong expertise with:
    • Embeddings
    • Vector databases
    • Retrieval pipelines
    • Prompt engineering
    • AI orchestration workflows
  • Strong Python programming skills
  • Experience with frameworks such as:
    • LangChain
    • LlamaIndex
    • PyTorch
  • Experience with:
    • CI/CD pipelines
    • Scalable model deployment
    • Monitoring and lifecycle management
    • MLOps best practices
Key Responsibilities
  • Design and deliver end-to-end AI/ML, Agentic AI, and LLM-based solutions
  • Translate business requirements into scalable AI architectures and measurable outcomes
  • Build RAG pipelines, vector search solutions, embeddings, and orchestration workflows
  • Develop prompt strategies, AI agents, workflow guardrails, and automation frameworks
  • Optimize AI systems for:
    • Performance
    • Scalability
    • Reliability
    • Cost efficiency
  • Implement monitoring, drift detection, CI/CD, and lifecycle management for AI models
  • Build production-grade data pipelines with validation, lineage, and reproducibility
  • Mentor engineering teams and drive responsible AI architecture and governance decisions
Preferred Skills
  • Experience with cloud AI platforms (AWS, Azure, or GCP)
  • Exposure to distributed AI systems and scalable inference architectures
  • Familiarity with Responsible AI and enterprise governance frameworks

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