MLops, Docker, Kubernetes, Python, LLM orchestration frameworks, LLMOps, vector databases, RAG pipelines, prompt engineering

Tensorflow, Azure ML, Pytorch, Python, embeddings, LLMs, scikit-learn, prompt engineering, vector stores, SageMaker, GCP Vertex AI, RAG, Cloud ML infrastructure

data engineering , Python, Fme, Databases, Cloud Services, Machine Learning, Apis, Qgis, Natural Language Processing, MLops, data pipelines, Azure OpenAI, Azure AI Foundry, LLM techniques, LangGraph, Azure cloud environments, Azure AI Search, Arcgis, LangChain, Generative AI, Agentic AI frameworks, AI ML engineering, Semantic Kernel, AutoGen

Nlp, Ml, Python, retrieval, LLM interfaces, agentic AI systems, LLM pipelines, memory evaluation, fine-tuning, prompt engineering, Evaluation

data engineering , Kafka, Python, AWS, Apis, Sql, MLops, Azure, RAG embeddings, anomaly detection, CI CD, LangGraph, Evaluation, event streaming architectures, structured outputs, observability, model monitoring, tool function calling, LLMs, LLMOps, SHAP feature attribution, retrieval evaluation, vector hybrid search, Classification, Semantic Kernel, prompt engineering, agentic workflows, Regression, Applied AI ML, gradient-boosting techniques, LlamaIndex

Azure, node.js, Gcp, Pytorch, Pyhton, aws, ml algorithms

AI Platform Infrastructure Engineering, MLOps LLMOps, Data Engineering Operationalization, Programming APIs, Automation Deployment Engineering, Security Governance

Machine Learning, Sql, Azure Sql, Numpy, Django, Git, Pandas, Azure Functions, Docker, Flask, Microsoft Azure, FastAPI, Rest Apis, Data Analytics, Python, Azure DevOps, Scikit-learn, App Service, CI CD pipelines