data engineering , Neural Networks, large-scale data processing frameworks and tools, data pipeline development and management in cloud and on-premise environments, AI-driven image processing, generative AI models, deep learning architectures, AI model integration and deployment techniques

Tensorflow, Pytorch, Gcp, MLops, Docker, Azure, Kubernetes, Python, AWS, LangChain, Generative AI, LLaMA, Scikit-learn, Pinecone, GPT, FAISS, LoRA, Weaviate, QLoRA, LlamaIndex, Large Language Models

Numpy, Git, Pandas, Databricks, Python, Sql, scikit-learn, AWS SageMaker, Vector databases, Similarity search concepts, NoSQL databases, Jupyter, Generative AI models

data engineering , Apis, Microservices, Gcp, Distributed Systems, System Design, Azure, Python, AWS, GenAI, embeddings, LLMs, cloud platforms, vector databases, SaaS-based architecture, Agentic AI, RAG