data engineering , Data Warehousing, Kafka, Docker, Python, AWS, Apache Spark, Sql, Software Engineering, Gcp, Rest Apis, Azure, Kubernetes, RAG frameworks, Qdrant, vector databases, MLflow, Pinecone, Kubeflow, Cloud MLOps, ETL pipelines, LangChain, Generative AI, LLMs, Clean code practices, prompt engineering, LLM fine-tuning, microservices architecture, Milvus, LlamaIndex

Pyspark, Tensorflow, Numpy, Nlp, Pytorch, Docker, XGBoost, Python, AWS, Scipy, Clustering, Sql, Git, Hive, Pandas, Gcp, Keras, Azure, Computer Vision, Random Forests, MLflow, Gradient Boosting, GLMs, R, Kubeflow, Vertex AI, EconML, BERT, LightGBM, Scikit-learn, DoWhy, SageMaker

Machine Learning, Deep Learning, MLops, Data Profiling, LangChain, Generative AI, Feature Engineering, LLMs, AI Agent Frameworks, GenAI Applications, LangGraph, RAG, OpenAI Gemini, Prompt Engineering

Machine Learning, Data Visualization, Big Data, Python, Sql, Deep Learning, Data Analysis, Statistical Modeling

Machine Learning, Natural Language Processing, Python, Deep Learning, Generative AI

Machine Learning, Apis, Python, GenAI, AI ML Models, RAG Models, Model Deployment, Ai, Lang Chain, Llm

snowflake , Github, Power Bi, Ms Office, Sql, Deep Learning, Python, AWS, cloud-native tools, Copilot, statistical and machine learning algorithms, Agentic AI, dbt

Nlp, Git, Python, Sql, Gcp, Azure, AWS, LLM fine-tuning

Spark SQL, Machine Learning, Pyspark, Microsoft Power Bi, Azure Databricks, Numpy, Pandas, MLops, Databricks, Python, Complex SQL, Azure ML Studio, Scikit-Learn, Statistical Modeling