Apis, Microservices, MLOps practices, RAG Retrieval-Augmented Generation solutions, vector databases, AI model integration, Generative AI applications

adobe target , optimizely , Tableau, Adobe Analytics, Python, Google Optimize, R

data engineering , Machine Learning, MLops, Algorithm Design, Deep Learning, Cloud Platforms, AI Ethics, Python Programming Language

MLops, Python Programming, Azure, AWS, Artificial Intelligence AI, RAG architecture, DevOps practices, Prompt Engineering and LLM Fine-Tuning, Google Cloud Platform GCP, Vector Databases, Generative AI GenAI, Intelligent Document Processing IDP, Machine Learning ML, Embedding Models

Summarization, Python, RAG components, LLM pipelines, citation grounding

data engineering , data curation , Machine Learning, Tensorflow, Data Science, Pytorch, Docker, Python, AWS, Redis, MLops, Gcp, Azure, Kubernetes, Similarity search algorithms, Agentic AI solution Architecture, Feature engineering, LangGraph, R, Optimization Techniques, LangChain, Generative AI, NoSQL databases, Responsible AI

snowflake , Docker, DevSecOps, MLops, Databricks, Kubernetes, AI Governance, Zero Trust Architecture, API Gateways, Azure OpenAI, Azure AI Foundry, LangGraph, AI Operations, cloud-native architectures, CrewAI, Generative AI, Platform Engineering Practices, Agentic AI frameworks, LLMs, Anthropic, Agentic AI Frameworks, OpenAI Agents, Semantic Kernel, AutoGen, Security by Design, OpenAI, Gemini, Open Source Models, Responsible AI Frameworks

Tensorflow, Numpy, Git, Pandas, Pytorch, Gcp, Azure, Python, AWS, LangChain, Langchain, Hugging Face Transformers, Scikit-learn, LlamaIndex, Langraph