data engineering , Machine Learning, Algorithms, Pandas, Data structures, Python, Standard ML algorithms, LLM-based solutions, Software design principles

Image Processing, Data Governance, Python, LLM pipelines, Deep learning neural networks, Machine learning frameworks, Chatbots, Cloud AI services, Versioning systems, Multi Cloud skills, Bias detection, Machine Learning Operations, Observability tools, Prompt management

triton , Pytorch, Kubernetes, Python, Docker, Qdrant, vLLM, LlamaIndex, Airflow, Weaviate, pgvector, LangChain, TGI, CrewAI, Pinecone, LangGraph, GPTQ, MLOps tools, Kubeflow, MLflow, quantization techniques, Scikit-learn, AWQ, Hugging Face ecosystem, AutoGen, GGUF, Weights Biases, FAISS

data engineering , Ml, FastAPI, Kubernetes, Python, AWS EKS, Nlp, Celery, Sqlalchemy, confidence calibration techniques, Airflow, Claude API, vector database, Ai, Pydantic, LLM output validation frameworks, embedding models, Weaviate, pgvector, semantic search, data ingestion pipelines, Pinecone, LLM evaluation frameworks, prompt engineering

AWS EKS, FastAPI, Kubernetes, Python, Celery, Sqlalchemy, Airflow, Claude API, confidence calibration techniques, Pydantic, LLM output validation frameworks, embedding models, Weaviate, pgvector, Pinecone, semantic search, RAG context

Artificial Intelligence, Machine Learning, Core Python, Python, Generative AI, Large Language Models, Llm, Generative AI Applications, RAG, Retrieval-Augmented Generation

Tensorflow, Ml, Sql, Deep Learning, AWS, Pytorch, Python, Nlp, Llm, DL, Langchain, RAG, Knowledge Graphs, Fast API, LangGraph

Github, Json, Tensorflow, Numpy, Git, Pandas, Gcp, Pytorch, Docker, Rest Apis, Azure, Kubernetes, Python, AWS, scikit-learn, LLM application patterns, RAG