Machine Learning, Nlp, Databricks, Python, AWS, LangChain, embeddings, GenAI, LangGraph, encoders-decoder models, retrieval-based systems, transformer architectures, Amazon Bedrock

Artificial Intelligence (AI), Data Science, Machine Learning, Numpy, Pandas, Matlab, R

Python, Sql, Bayesian causal modeling, R, uplift modeling, cloud-based data platforms, regression-based models, causal inference techniques

Pytorch, Data Visualization, Python, Sql

Java, Sql, Numpy, Pandas, Pytorch, Javascript, Docker, Keras, Python, Langchain, scikit-learn, OpenAI API, RAG

PostgreSQL, Rdf, Neo4j, Python, AWS, Apis, Gcp, MLops, Azure, pgvector, LLM-driven applications, vector databases, Pinecone, GenAIOps, LangGraph, Chroma, GenAI microservices, RAG pipelines, architecture standards, LangChain, knowledge-grounding frameworks, cloud platforms, benchmark model performance, prompt engineering, knowledge graph systems, Transformers, Milvus, Weaviate, LlamaIndex

tokenization , SAS, Sql, Deep Learning, Hive, Spark, Machine Learning, Natural Language Processing, Python, NLP based n-grams methodology, Data Analysis, Statistical models, Fuzzy matching, R, Similarity scoring, phonetics

Databricks, Sql, Natural Language Processing, Tensorflow, Tableau, Deep Learning, Power Bi, AWS, Pytorch, Python, Azure, Git, Spark, machine learning frameworks, scikit-learn, data pipeline development, R, LLM Agentic AI, DevOps practices, ETL processes