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Ai Rag Jobs in Melbourne, FL (NOW HIRING)

540

Senior Software Engineer (AI/ML)

Satellite Beach, FL · On-site

$113K - $149K/yr

Experience with, or a strong conceptual understanding of, LLM-based applications, RAG pipelines, and AI-driven decision systems * Experience with Python * Experience working with relational databases ...

L3HHCM20

Specialist, Application Developer

Melbourne, FL · On-site

$92K - $171K/yr

Knowledge of agentic AI frameworks (LangChain, LangGraph, AutoGPT, CrewAI, etc.) * Experience with vector databases and RAG architecture * Familiarity with prompt engineering techniques and LLM fine ...

L3HHCM20

Lead, Data Engineer

Melbourne, FL · Remote

$127K - $236K/yr

Experience supporting or implementing solutions that leverage Generative AI capabilities, including Retrieval-Augmented Generation (RAG), semantic search, and LLM integration * Experience with ...

L3HHCM20

Principal, Data Engineer

Melbourne, FL · On-site +1

$153K - $284K/yr

Experience architecting Palantir Foundry platforms to enable Generative AI capabilities, including Retrieval-Augmented Generation (RAG), semantic search, and LLM integration * Experience with ...

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Ai Rag information

See Melbourne, FL salary details

$29.7K

$54K

$77.4K

How much do ai rag jobs pay per year?

As of Aug 10, 2026, the average yearly pay for ai rag in Melbourne, FL is $53,989.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,400.00 and $60,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI researcher?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What is an AI RAG?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What job categories do people searching Ai Rag jobs in Melbourne, FL look for? The top searched job categories for Ai Rag jobs in Melbourne, FL are:
What cities near Melbourne, FL are hiring for Ai Rag jobs? Cities near Melbourne, FL with the most Ai Rag job openings:
Ai Rag jobs near you

Artificial Intelligence (AI) Engineer III (2316)

Morson Talent

Melbourne, FL • Hybrid

$55 - $62/hr

Full-time

Re-posted 7 days ago

Job description

Job Description Title: Artificial Intelligence (AI) Engineer III (2316) Location: Melbourne, Florida Openings: 1 Work Model: Hybrid, 2 - 3 days in office Job Type: Contract Duration: 1 Year Rate: $61/hour (W2) + Benefits Hours: 40 hours/week, 8 - 5 Project: Technology Division Position Summary: An AI (Artificial Intelligence) Engineer develops and trains AI models to automate processes and solve complex problems. They design and implement AI systems, ensuring they function effectively and align with business objectives. Responsibilities: Evaluate machine learning processes and select appropriate models.

Collect and analyze large datasets to train AI models. Develop and deploy AI algorithms and systems. Collaborate with cross functional teams to establish goals for AI processes.

Test and validate AI models to ensure accuracy and effectiveness. Manage data and project infrastructure. Stay updated on the latest AI developments and technologies.

Strong Large Language Model (LLM) Expertise Handson experience finetuning, adapting, and deploying LLMs, including prompt engineering, embeddings, and context management. LLM Application & System Architecture Proven ability to design and implement productiongrade LLM solutions such as RAG pipelines, agents, and tool/functioncalling systems. Production MLOps & Model Lifecycle Management Experience owning the endtoend ML lifecycle, including CI/CD, deployment, monitoring, versioning, and performance/cost optimization.

Advanced Python & Software Engineering Strong Python skills with experience building scalable, testable APIs and services that integrate ML/LLM models into enterprise systems. CloudBased Scalable ML Infrastructure Handson experience with AWS, Azure, or GCP, including containerization (Docker), orchestration (Kubernetes), and GPUbased ML workloads. Qualifications: Masters degree in Computer Science, Engineering, or a related field.

Proven experience as an AI Engineer or in a similar role. Strong programming skills in languages such as Python, R, or Java. Experience with machine learning frameworks and libraries.

Excellent analytical and problem-solving abilities. Effective communication and collaboration skills.

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