Machine Learning, Api Development, Gcp, Azure, Python, AWS, AI orchestration frameworks, Generative AI, LLMs, vector databases, prompt engineering, Agentic AI, RAG architectures

Gcp, MLops, Pytorch, Azure, Python, AWS, LangChain, AutoGen, Transformers, DSPy, LlamaIndex, AIOps, Haystack

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

FastAPI, Python, LangChain, Tool Calling, Agents, Vector Search, RAG Retrieval, LLM Evaluation, LangGraph, Document AI, Embeddings, LLM APIs, Structured Outputs

Testing, Git, Docker, Kubernetes, LangChain, RAG systems, Crew.ai, embedding models, vector databases, Anthropic, knowledge retrieval systems, safety considerations, prompt engineering, Autogen, development frameworks, Advanced Python programming, LLM optimization techniques, OpenAI, async programming, RAG pipelines, semantic search, agent alignment

Apis, Microservices, Rest Apis, Python, LLM and agent evaluation frameworks, model governance, LLMs, multi-agent orchestration, agent memory design, enterprise data concepts, tool-calling capabilities, agent development frameworks, GenAI applications, observability and tracing, guardrails for AI agents

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

Information Retrieval, Pyspark, Data Cleaning, Sql, Databricks, Python, Etl, Airflow, workflow orchestration tools, RAG frameworks, knowledge graphs, LLMs, vector databases, machine learning fundamentals, production-grade AI solutions, Temporal, dbt, feature engineering