Api Development, Python, embeddings, Generative AI, AWS Bedrock, LLMs, RAG, vector databases, retrieval mechanisms, Prompt Engineering

Python, AWS, Graphql, Api Integration, REST, Gcp, MLops, Azure, LLM-based systems, Qdrant, vector databases, Pinecone, LangGraph, ChromaDB, semantic search, LangChain, CrewAI, Generative AI, embedding models, prompt engineering, AutoGen, FAISS, Milvus, Weaviate

LangChain

Api Integration, Gcp, MLops, System Design, Azure, Python, AWS, embeddings, Generative AI, LLMs, RAG systems, Hugging Face, vector databases, Claude, GPT, Azure OpenAI, semantic search technologies, OpenAI, fine-tuning techniques, evaluation metrics, deployment pipelines, model monitoring

Machine Learning, MongoDB, Python, AWS, Generative AI, LLMs, AI architectures

Python, LangChain, LLM Application Development, AutoGen or equivalent, Agentic Multi-step AI Workflows, REST API Integration, RAG Retrieval Augmented Generation, AI Telemetry Monitoring, Prompt Engineering

Microservices, Java, Testing, Kubernetes, Docker, Git, async programming, RAG pipelines, Crew.ai, cloud-native architecture, knowledge retrieval systems, embedding models, vector databases, RAG systems, LLM optimization techniques, LangChain, Autogen, prompt engineering, advanced Python programming

Git, Docker, Kubernetes, Python, LangChain, LLM optimization techniques, RAG systems, vector databases, embedding models, prompt engineering

Tensorflow, Nlp, Pytorch, Docker, Python, AWS, Gcp, Azure, Kubernetes, GloVe, Hugging Face, MLflow, Pinecone, MLOps practices, LLM architecture, Word2Vec, RAG pipelines, ChromaDB, fine-tuning techniques, APIs from major AI providers, LangChain, LLM training methodologies, LoRA, QLoRA, sentence transformers, cloud computing platforms

Pytorch, Linux, Docker, Python Programming, PEFT, Hugging Face Transformers, open-source LLMs, model routing, prompt engineering, GPU-based inference and optimization, Evaluation, structured extraction, LoRA, NVIDIA GPU infrastructure, reranking, RAG, Generative AI LLMs