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Freelance Retrieval Augmented Generation Jobs (NOW HIRING)

Futran Tech Solutions Pvt. Ltd.

Data Scientist

Additionally, experience in building Retrieval-Augmented Generation (RAG) pipelines for search and chat applications is highly desired. Key Responsibilities: * Develop and optimize NLP models for ...

TekShapers

Gen AI Architect

Raritan, NJ · On-site

Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases and enterprise data sources. * Collaborate with business stakeholders, product teams, and engineering ...

CYNET SYSTEMS

Senior AI Engineer - Privacy

Bellevue, WA · On-site

$70 - $75/hr

This role involves applying large language models, retrieval-augmented generation, multi-agent orchestration, and foundation model capabilities to automate and enhance privacy operations. Requirement ...

Tekshapers Inc

Generative AI/ML Engineer

New York, NY · On-site

The ideal candidate will have a strong background in investment banking, hands-on experience with Microsoft Azure OpenAI, and expertise in Retrieval-Augmented Generation (RAG). Key Responsibilities:

Compunnel

Senior Data Scientist GenAI / RAG

Houston, TX · On-site

Build, deploy, and optimize Retrieval-Augmented Generation (RAG) systems and AI-powered chat interfaces. * Develop enterprise Generative AI solutions using Large Language Models (LLMs) and related ...

SansuTek Inc.

Prompt Engineer

Fort Worth, TX · On-site

Retrieval Augmented Generation (RAG) and vector search * Vector databases & embeddings (Azure) * LLM evaluation, latency optimization, cost management, hallucination mitigation * AI governance, PII ...

New

Pereview Software

AI Engineer

Dallas, TX

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Redolent, Inc.

Sr, ML Architect

Washington, DC · On-site

Integrate with large language models (LLMs) and generative AI (GenAI) using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) techniques. * Implement MCP client and server ...

CGI

GenAI Context Engineer

Pittsburgh, PA · On-site

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. . Build and optimize semantic retrieval pipelines, vector search ...

CGI Inc.

GenAI Context Engineer

Pittsburgh, PA · On-site

Design and implement enterprise Retrieval Augmented Generation (RAG) architectures for GenAI platforms and applications. . Build and optimize semantic retrieval pipelines, vector search ...

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Carter Support Services

AI/ML Engineer

Burbank, CA · On-site

$111K - $153K/yr

Build and deploy RAG (Retrieval-Augmented Generation) pipelines * Integrate LLMs via APIs (Azure OpenAI preferred) into enterprise applications * Develop and orchestrate agentic AI workflows with ...

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Freelance Retrieval Augmented Generation information

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How much do freelance retrieval augmented generation jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for freelance retrieval augmented generation in the United States is $22.97, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $18.75 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Freelance Retrieval Augmented Generation Specialist, and why are they important?

To thrive as a Freelance Retrieval Augmented Generation (RAG) Specialist, you need expertise in natural language processing, information retrieval, and machine learning, typically supported by a degree in computer science or related fields. Proficiency with frameworks like Hugging Face Transformers, vector databases (e.g., FAISS, Pinecone), and cloud platforms is often required. Strong problem-solving, effective communication, and adaptability set standout professionals apart in this role. These skills ensure the development and fine-tuning of high-performance RAG systems that deliver accurate, contextually relevant results for clients.

What is a Freelance Retrieval Augmented Generation (RAG) specialist?

A Freelance Retrieval Augmented Generation (RAG) specialist is an independent professional who designs, develops, and implements AI systems that combine retrieval-based methods with generative models. RAG specialists help organizations enhance their applications by integrating large language models (LLMs) with external data sources, allowing the AI to access and utilize up-to-date information beyond its training data. Their work involves tasks such as building pipelines for document indexing and retrieval, fine-tuning models, and optimizing the integration for accuracy and efficiency. Freelance RAG specialists typically work on a contract basis, offering flexibility and expertise for businesses that need advanced AI solutions.

How do Freelance Retrieval Augmented Generation specialists typically collaborate with client teams during a project?

Freelance Retrieval Augmented Generation (RAG) specialists often work closely with client data scientists, engineers, and project managers to understand business requirements and integrate RAG systems into existing workflows. Communication is usually handled through regular virtual meetings, shared documentation, and sometimes real-time collaboration tools. Freelancers are expected to deliver modular, well-documented solutions and provide guidance on optimizing retrieval pipelines or fine-tuning models. This collaborative dynamic ensures that RAG implementations are aligned with client goals and technical standards, while also allowing freelancers to contribute innovative solutions based on their expertise.
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Freelance Retrieval Augmented Generation jobs near you
Infographic showing various Freelance Retrieval Augmented Generation job openings in the United States as of July 2026, with employment types broken down into 90% Full Time, 8% Part Time, and 2% Contract. Highlights an 77% Physical, 3% Hybrid, and 20% Remote job distribution, with an average salary of $47,772 per year, or $23 per hour.

Data Scientist

Futran Tech Solutions Pvt. Ltd.

Remote

Full-time

Re-posted yesterday

Job description

New Demand - Data Scientist
Remote
  • Total Years of experience 10-12 years
  • 6 months+
  • Occasional travel to the client location is required.
  • Candidates might need to overlap with offshore on need basis.

Must have skills : Elastic Search, Generative AI Fundamentals (Strong), Python for Data Science (Strong), RAG, Vector Illustration Good to have skills:
Job Description :
  • Data Scientist with ~6+ years of expertise in Natural Language Processing (NLP), Large Language Models (LLMs), and Generative AI (GenAI).
  • The ideal candidate will have hands-on experience with search-related work, including relevance tuning, text classification, and topic modeling.
  • Additionally, experience in building Retrieval-Augmented Generation (RAG) pipelines for search and chat applications is highly desired. Key Responsibilities:
  • Develop and optimize NLP models for text classification, text clustering, topic modeling, and relevance tuning in search.
  • Work with LLMs to build advanced generative AI solutions for search and chat applications.
  • Design and implement Retrieval-Augmented Generation (RAG) pipelines to improve search and conversational AI systems.
  • Collaborate with cross-functional teams to deploy data-driven search enhancements and GenAI solutions.
  • Analyze and fine-tune search relevance based on user behavior and search intent from querylog.

Qualifications:
  • Experience in running and fine-tuning models from Hugging face
  • Familiarity with building and deploying RAG pipelines
  • Familiarity with vector databases like Elasticsearch, Pinecone, etc.
  • Strong programming skills (e.g., Python, TensorFlow, PyTorch, SQL)
  • Experience in model deployment & MLOps is a plus
  • Experience with cloud platforms (AWS) is a plus.

Let me know if you have any questions.

Apply