containerization , Tensorflow, Pytorch, Docker, Python, AWS, Gcp, Azure, Kubernetes, embeddings, Hugging Face, MLflow, vector databases, Ray, Pinecone, model evaluation, MLOps tools, RAG pipelines, Building and deploying AI agents, NLP concepts, AI ML frameworks, LangChain, OpenAI Assistants, cloud platforms, prompt engineering, AutoGen, FAISS, Milvus, Fine-tuning LLMs, Weaviate

Python, large-scale software systems, MLOps practices, API and system architecture, high-quality maintainable code, AI solutions

Pytorch, MLops, Python, Deep Learning, Generative AI, Langchain, LMM, Llm

Java, Spring Boot, Sql, Nosql, Tensorflow, Numpy, Git, Pandas, Pytorch, Gcp, MLops, Docker, Azure, Kubernetes, Python, AWS, scikit-learn, AI ML Expertise, Agentic AI, Microservices Architecture

PostgreSQL, Microservices, Git, Tdd, Docker, Kubernetes, Python, LLMs, Pinecone, RAG, Azure AI Search, Prompt Engineering

Gcp, MLops, Docker, Flask, FastAPI, Azure, Python, Kubernetes, AWS, LangChain, Generative AI, LLMOps, RAG fine-tuning, LLM techniques, LangGraph, Vertex AI, Microsoft Agent Framework, Claude SDK

Python, AI model deployment

Docker, Flask, FastAPI, Kubernetes, LangChain, Azure OpenAI APIs, Hugging Face, Pinecone, Vector Database integration, CI CD pipelines, Python 3.9, Milvus, OpenAI, LlamaIndex

Python development, Containerization and Kubernetes environments, CI CD pipelines and version control workflows, Model serving or inference runtime concepts, Vector database usage and embedding pipelines, RAG concepts including embedding and retrieval, Monitoring logging and tracing fundamentals

Machine Learning, Nodejs, API design, Nlp, Gcp, Docker, FastAPI, Azure, Python, Kubernetes, Computer Vision, AWS, Generative AI, Applied AI, AI Systems Engineering