Gcp, Azure, AWS, Data engineering pipeline development, Bias mitigation, Deploying LLMs for specific applications, Responsible AI practices, Knowledge of AI Ethics

Numpy, Gcp, Pandas, FastAPI, Azure, Python, AWS, embeddings, LLMs, cloud platforms, prompt engineering, Generative AI solutions, retrieval techniques

Devops, Databases, React, Typescript, Apis, Javascript, Node.js, Python

Apis, Workflows, Databricks, LangGraph, LangChain, Copilots, Chatbots, OpenAI, Azure OpenAI, Prompt Engineering

Java 8, Git, Rest Apis, LangChain, Pinecone, GenAI concepts, LangGraph, Vector Databases, RAG Retrieval-Augmented Generation, Microservices Architecture, FAISS, CI CD pipelines, LLM integrations, Weaviate

Gcp, Python Programming, AWS, CrewAI, Evaluation, LangChain, Document Intelligence, Azure AI Stack, LLMOps, Logic Apps, Agentic Frameworks, Azure Function Apps, RAGAS, Foundry ML, LangSmith, LangGraph, Google Cloud Platform GCP, Vision, RAG, AI Search

Microservices, Tensorflow, Pytorch, Python, Apis, Functions, Azure ML, MLops, Azure, Qdrant, vector databases, Pinecone, CI CD, NLP pipelines, LLM-powered applications, Hugging Face models, LangChain, traditional ML techniques, Azure OpenAI GPT-based APIs, Cognitive Services, AKS, Semantic Kernel, FAISS, Milvus, Weaviate, LlamaIndex

AI ML, Data Quality, AWS, Kubernetes, Azure, Docker, Gcp, Apis, CI CD pipelines, Model versioning, Microservices architectures, Monitoring and observability solutions, Data pipelines, SDKs, ML Ops, Experiment tracking