Logging, Jenkins, Nlp, Azure Cloud, Storage, Flask, FastAPI, Cosmos DB, Generative AI, LLMs, Monitoring, CI CD, prompt engineering, async, App Service, OpenTelemetry, Azure OpenAI LLM platforms, RAG, Python advanced, AI Search

Github, Apis, Tensorflow, Numpy, Git, Pandas, MLops, Pytorch, Docker, Azure, Kubernetes, Python, AWS, agentic architecture, GenAI, scikit-learn, LLMOps, Llm, distributed services, infrastructure as code

RAG (Retrieval-Augmented Generation), Python Programming, metrics, evaluation datasets, fine-tuning, AI fundamentals, production ML systems, Llm, AI agent architecture, model evaluation, structured testing, benchmarks, root-cause analysis, model improvement

text classification , Pytorch, Embedded Linux, Nlp, Python, LLM RAG Pipelines, LangChain, Hugging Face, TensorRT, Quantization, Model Fine-tuning, NVIDIA Jetson Platforms, ONNX, Vector Databases, Jetson Nano, ONNX Runtime, LLM Deployment, RAG, Real-time AI Applications, Edge AI Optimization, Prompt Engineering, NER

Azure Cosmos DB, Docker, Microsoft Azure, Python, Azure DevOps, Azure Sql, MLops, Azure Machine Learning, Kubernetes, Vector search, MLflow, Pinecone, Azure OpenAI, CI CD, Azure AI Search, Haystack, LangChain, Prompt Flow, RAG architecture, Vector databases, Semantic search techniques, Semantic Kernel, Azure AI Services, FAISS, Embedding models, Weaviate, LlamaIndex

PostgreSQL, Docker, FastAPI, Kubernetes, Python, LangChain, embedding strategies, pgvector, observability practices, RAG pipeline architecture, prompt lifecycle management, vector database selection, Azure OpenAI, LangGraph, LLM engineering, retrieval strategies, context management strategies, LLM evaluation

probability , Testing Frameworks, Deep Learning, prompt engineering, AI evaluation methodologies, cloud-native AI architectures, RAG techniques, fine-tuning model adaptation, LLM customization, AI model monitoring, deploying ML models as APIs, production-quality AI code, vector databases, linear algebra, Governance, AI pipelines, ML algorithms, drift detection, LLM architectures

Azure, Machine Learning, Tensorflow, Pytorch, Gcp, Python, AWS, Generative AI, Prompt engineering, scikit-learn, LLM integration, RAG pipelines, Fine-tuning