Python, ethical AI frameworks, Responsible AI, industry standards, Regulatory Requirements, risk assessment methodologies

Gcp, Flask, FastAPI, Azure, Python, AWS, LangChain, embeddings, LLMs, Hugging Face, vector databases, Anthropic, Pinecone, Claude, LangGraph, FAISS, RAG, Streamlit, ChromaDB, semantic search

Docker, Restful Apis, LangChain, AI ML or LLM-based systems, NoSQL databases, vector databases, PGVector, prompt engineering, LangGraph, Azure OpenAI Gemini, GitHub Actions, Agile product teams, CI CD pipelines, distributed API-driven systems, MCP and A2A communication models, RAG pipelines, Azure AI Search

Predictive Modeling, Machine Learning, MLops, Natural Language Processing, Python, Sql, Deep Learning, anomaly detection, Vector Databases, Data Pipelines, Model Deployment

Kubernetes, Python, Airflow, Generative AI, GitHub-based workflows, Applied AI, Data pipelines, Cloud-based development

Pandas, Python, LangChain, Generative AI, AI ML concepts, LLMs

Pandas, Pytorch, Gcp, Docker, Python, Generative AI, Huggingface Transformers, Scikit-learn

PostgreSQL, Containers, Kafka, Neo4j, MongoDB, FastAPI, Cosmos DB, Azure, API-based model integration, K8S, secure deployment practices, observability needs, DevOps tooling, RAG agentic workflows, environment management, CI CD pipelines, AI solutions

object detection , Ml, Tensorflow, Computer Vision, Pytorch, Docker, Opencv, Azure, Kubernetes, AWS, Ai, TensorRT, anomaly detection, ONNX, Segmentation

Pytorch, Python, LoRA, BLIP, Stable Diffusion, CLIP