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

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

Microservices, Terraform, Python, AWS, Rust, Cloudformation, Jenkins, Git, Gcp, FastAPI, Azure, Kubernetes, RAG systems, Hugging Face Transformers, Go, MLflow, TF Serving, embedding optimization, vector database management, GitHub Actions, dimensionality reduction, TorchServe, LangChain, big data processing using Spark, vLLM, test-driven development, model quantization techniques, CI CD pipelines, concurrency processing

Java, Github, PostgreSQL, Pl Sql, Spring Boot, Jira, Jacoco, Angular, Jenkins, Git, Docker, Sonarqube, Oracle, Python, Ai, GitLab CI

Api Integration, Python, LangChain, CrewAI, ethical AI principles, LLMs, reasoning algorithms, Planning Systems, reinforcement learning, prompt engineering, AutoGen, tool augmentation, fine-tuning techniques, safety mechanisms, agentic frameworks, AI ML frameworks

Gen AI, AI and Machine Learning algorithms, RAG neural networks

Machine Learning, Deep Learning, Python, Transfer Learning, Feature Engineering, reinforcement learning, Model Fine-tuning, Generative Models, Data Applications, Data Processing, Streamlit, Prompt Engineering

Scala, Pyspark, Sql, Azure ML, Gcp, Spark, Azure, Python, AWS, Airflow, ML Ops, Kubeflow, MLFlow

snowflake , MLops, Docker, Terraform, Data Integration, Azure, AWS, generative AI, data orchestration