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Delegate expert-level AI/ML workflows to specialized agents: engineer optimized prompts with evaluation and A/B testing, architect scalable LLM systems with RAG/LoRA fine-tuning, build production NLP pipelines for NER/classification/QA, and deploy optimized models via vLLM/Triton/Docker/K8s for reliability, performance, and cost control.
npx claudepluginhub nodnarbnitram/claude-code-extensions --plugin cce-aiExpert AI engineer specializing in AI system design, model implementation, and production deployment. Masters multiple AI frameworks and tools with focus on building scalable, efficient, and ethical AI solutions from research to production.
Expert LLM architect specializing in large language model architecture, deployment, and optimization. Masters LLM system design, fine-tuning strategies, and production serving with focus on building scalable, efficient, and safe LLM applications.
Expert ML engineer specializing in production model deployment, serving infrastructure, and scalable ML systems. Masters model optimization, real-time inference, and edge deployment with focus on reliability and performance at scale.
Expert NLP engineer specializing in natural language processing, understanding, and generation. Masters transformer models, text processing pipelines, and production NLP systems with focus on multilingual support and real-time performance.
Expert prompt engineer specializing in designing, optimizing, and managing prompts for large language models. Masters prompt architecture, evaluation frameworks, and production prompt systems with focus on reliability, efficiency, and measurable outcomes.
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Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Data engineering, ML, and AI specialists - data pipelines, machine learning, LLM architecture
Deploy ML models to production
ML engineering agents providing expertise in MLOps, model deployment, and inference optimization
Agents for data engineering, machine learning, and AI development
Use this agent when implementing AI/ML features, integrating language models, building recommendation systems, or adding intelligent automation to applications. This agent specializes in practical AI implementation for rapid deployment. Examples:\n\n<example>\nContext: Adding AI features to an app\nuser: "We need AI-powered content recommendations"\nassistant: "I'll implement a smart recommendation engine. Let me use the ai-engineer agent to build an ML pipeline that learns from user behavior."\n<commentary>\nRecommendation systems require careful ML implementation and continuous learning capabilities.\n</commentary>\n</example>\n\n<example>\nContext: Integrating language models\nuser: "Add an AI chatbot to help users navigate our app"\nassistant: "I'll integrate a conversational AI assistant. Let me use the ai-engineer agent to implement proper prompt engineering and response handling."\n<commentary>\nLLM integration requires expertise in prompt design, token management, and response streaming.\n</commentary>\n</example>\n\n<example>\nContext: Implementing computer vision features\nuser: "Users should be able to search products by taking a photo"\nassistant: "I'll implement visual search using computer vision. Let me use the ai-engineer agent to integrate image recognition and similarity matching."\n<commentary>\nComputer vision features require efficient processing and accurate model selection.\n</commentary>\n</example>
ML engineering plugin: Give your AI coding agent ML engineering superpowers.
TypeScript and frontend tooling including Braintrust testing and fumadocs documentation
Essential Claude Code extensions: core agents, hooks, commands, and universal tools
Kubernetes cluster operations, health diagnostics, and operator-specific agents
DevOps tooling: GitHub Actions, Helm, ArgoCD, and Crossplane for CI/CD and infrastructure
Vue.js and Nuxt.js development with Composition API, composables, and SSR/SSG patterns
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