... optimize LLM-powered systems, including RAG pipelines, fine-tuned models, and enterprise AI ... Required : • Deep technical expertise in AI/ML • Strong architectural vision • Hands-on ...
... optimize LLM-powered systems, including RAG pipelines, fine-tuned models, and enterprise AI ... Required : • Deep technical expertise in AI/ML • Strong architectural vision • Hands-on ...
... RAG), embeddings/vector search, document extraction tools (Azure Document Intelligence, Textract ... ML Models on a cloud environment o Experience in GenAI/LLM (Claude, Gemini, and Llama 3.x) o Strong ...
... RAG), embeddings/vector search, document extraction tools (Azure Document Intelligence, Textract ... ML Models on a cloud environment o Experience in GenAI/LLM (Claude, Gemini, and Llama 3.x) o Strong ...
Llm Ml Rag information
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?
| Aspect | Llm Ml Rag | Data Scientist |
|---|---|---|
| Required Credentials | Master's or PhD in ML, AI, or related fields; certifications in ML frameworks | Degree in Computer Science, Statistics, or related; certifications in data analysis or ML |
| Work Environment | Research labs, AI development teams, tech companies | Business analytics, research, product development teams |
| Employer & Industry Usage | Tech firms, AI startups, research institutions | Finance, healthcare, tech, consulting firms |
| Common Search & Comparison | Often compared for ML specialization and research focus | Compared 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 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 is an llm ml rag job?
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.
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What job categories do people searching Llm Ml Rag jobs in Iowa look for? The top searched job categories for Llm Ml Rag jobs in Iowa are:
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Job description
Job Summary:
ClifyX is seeking a highly accomplished Principal AI Engineer to lead the design, architecture, and delivery of enterprise scale AI and Machine Learning solutions. This role requires deep technical expertise in AI/ML, strong architectural vision, and hands-on leadership to drive AI strategy across the organization.
Responsibilities:
• Define and drive the organization's AI roadmap, architecture, and long-term technical vision.
• Lead and mentor AI/ML engineers, data scientists, and cross-functional teams.
• Evaluate emerging technologies and guide adoption of GenAI, LLMs, MLOps frameworks, and AI platforms.
• Architect scalable, high-performance machine learning and GenAI solutions for NLP, CV, predictive analytics, and automation.
• Design and optimize LLM-powered systems, including RAG pipelines, fine-tuned models, and enterprise AI assistants.
• Develop reusable AI frameworks, components, and internal toolkits to accelerate organization-wide AI development.
• Oversee full lifecycle: data architecture, feature engineering, experimentation, training, validation, deployment, and monitoring.
• Build large-scale, cloud-native AI systems using Azure/AWS/GCP.
• Establish standards for model quality, reliability, interpretability, and governance.
• Architect robust MLOps pipelines—CI/CD, model versioning, drift detection, automated retraining, monitoring.
• Lead the development of AI platforms supporting multiple business teams and workloads.
• Ensure production environments meet performance, scalability, and security requirements.
• Partner with executives, product teams, and business leaders to identify AI opportunities.
• Translate complex business problems into scalable AI solutions.
• Represent AI architecture in technical reviews and decision-making processes.
Qualifications:
Required:
• Deep technical expertise in AI/ML
• Strong architectural vision
• Hands-on leadership
• Ability to drive AI strategy across the organization
• Extensive experience with advanced ML systems
• Experience with GenAI/LLM solutions
• Experience with end to end AI platform development
• Define and drive the organization's AI roadmap, architecture, and long-term technical vision
• Lead and mentor AI/ML engineers, data scientists, and cross-functional teams
• Evaluate emerging technologies and guide adoption of GenAI, LLMs, MLOps frameworks, and AI platforms
• Architect scalable, high-performance machine learning and GenAI solutions for NLP, CV, predictive analytics, and automation
• Design and optimize LLM-powered systems, including RAG pipelines, fine-tuned models, and enterprise AI assistants
• Develop reusable AI frameworks, components, and internal toolkits to accelerate organization-wide AI development
• Oversee full lifecycle: data architecture, feature engineering, experimentation, training, validation, deployment, and monitoring
• Build large-scale, cloud-native AI systems using Azure/AWS/GCP
• Establish standards for model quality, reliability, interpretability, and governance
• Architect robust MLOps pipelines—CI/CD, model versioning, drift detection, automated retraining, monitoring
• Lead the development of AI platforms supporting multiple business teams and workloads
• Ensure production environments meet performance, scalability, and security requirements
• Partner with executives, product teams, and business leaders to identify AI opportunities
• Translate complex business problems into scalable AI solutions
• Represent AI architecture in technical reviews and decision-making processes
• Experience with Databricks, SQL, and data processing frameworks
Company:
ClifyX provides innovative business solutions which satisfy requirements for mission-critical reliability, scalability, interoperations. Founded in 1998, the company is headquartered in South Plainfield, USA, with a team of 501-1000 employees. The company is currently Late Stage.
ClifyX is seeking a highly accomplished Principal AI Engineer to lead the design, architecture, and delivery of enterprise scale AI and Machine Learning solutions. This role requires deep technical expertise in AI/ML, strong architectural vision, and hands-on leadership to drive AI strategy across the organization.
Responsibilities:
• Define and drive the organization's AI roadmap, architecture, and long-term technical vision.
• Lead and mentor AI/ML engineers, data scientists, and cross-functional teams.
• Evaluate emerging technologies and guide adoption of GenAI, LLMs, MLOps frameworks, and AI platforms.
• Architect scalable, high-performance machine learning and GenAI solutions for NLP, CV, predictive analytics, and automation.
• Design and optimize LLM-powered systems, including RAG pipelines, fine-tuned models, and enterprise AI assistants.
• Develop reusable AI frameworks, components, and internal toolkits to accelerate organization-wide AI development.
• Oversee full lifecycle: data architecture, feature engineering, experimentation, training, validation, deployment, and monitoring.
• Build large-scale, cloud-native AI systems using Azure/AWS/GCP.
• Establish standards for model quality, reliability, interpretability, and governance.
• Architect robust MLOps pipelines—CI/CD, model versioning, drift detection, automated retraining, monitoring.
• Lead the development of AI platforms supporting multiple business teams and workloads.
• Ensure production environments meet performance, scalability, and security requirements.
• Partner with executives, product teams, and business leaders to identify AI opportunities.
• Translate complex business problems into scalable AI solutions.
• Represent AI architecture in technical reviews and decision-making processes.
Qualifications:
Required:
• Deep technical expertise in AI/ML
• Strong architectural vision
• Hands-on leadership
• Ability to drive AI strategy across the organization
• Extensive experience with advanced ML systems
• Experience with GenAI/LLM solutions
• Experience with end to end AI platform development
• Define and drive the organization's AI roadmap, architecture, and long-term technical vision
• Lead and mentor AI/ML engineers, data scientists, and cross-functional teams
• Evaluate emerging technologies and guide adoption of GenAI, LLMs, MLOps frameworks, and AI platforms
• Architect scalable, high-performance machine learning and GenAI solutions for NLP, CV, predictive analytics, and automation
• Design and optimize LLM-powered systems, including RAG pipelines, fine-tuned models, and enterprise AI assistants
• Develop reusable AI frameworks, components, and internal toolkits to accelerate organization-wide AI development
• Oversee full lifecycle: data architecture, feature engineering, experimentation, training, validation, deployment, and monitoring
• Build large-scale, cloud-native AI systems using Azure/AWS/GCP
• Establish standards for model quality, reliability, interpretability, and governance
• Architect robust MLOps pipelines—CI/CD, model versioning, drift detection, automated retraining, monitoring
• Lead the development of AI platforms supporting multiple business teams and workloads
• Ensure production environments meet performance, scalability, and security requirements
• Partner with executives, product teams, and business leaders to identify AI opportunities
• Translate complex business problems into scalable AI solutions
• Represent AI architecture in technical reviews and decision-making processes
• Experience with Databricks, SQL, and data processing frameworks
Company:
ClifyX provides innovative business solutions which satisfy requirements for mission-critical reliability, scalability, interoperations. Founded in 1998, the company is headquartered in South Plainfield, USA, with a team of 501-1000 employees. The company is currently Late Stage.
About ClifyX
Sourced by ZipRecruiter
ClifyX is a well-established player in the IT Services sector that specializes in providing result-oriented technological solutions to a wide range of industrial verticals. Based in South Plainfield, New Jersey, ClifyX offers a comprehensive selection of IT services that include project staffing, application development, professional consulting, and other IT-based solutions. While the company's website, clifyx.com, does not divulge the exact founding date, it is clear that ClifyX has grown into a renowned name within their domain, thanks to their unwavering commitment to innovative practices. The company's mission statement revolves around harnessing the power of technology to assist their clientele in steering their respective businesses towards success.
Industry
Recruiting and staffing services
Company size
51 - 200 Employees
Headquarters location
South Plainfield, NJ, US
Year founded
1998