Ml, Tensorflow, MLops, Pytorch, Gcp, Azure, Kubernetes, Python, AWS, GenAI, scikit-learn, Llm

snowflake , Sql, Tensorflow, Pandas, Pytorch, Spark, Python, Scikit-learn, vector databases, MLflow, prompt engineering, Agentic AI systems, MLOps practices, MCP Model Context Protocol, LLM-powered applications, Kubeflow, Generative AI LLM Proficiency, RAG pipelines

snowflake , Sql, Tensorflow, Pandas, Pytorch, Spark, Python, Scikit-learn, MLflow, vector databases, prompt engineering, Agentic AI systems, MCP Model Context Protocol, MLOps practices, LLM-powered applications, Kubeflow, Generative AI LLM Proficiency, RAG pipelines

data engineering , Machine Learning, Tableau, Tensorflow, Numpy, Pytorch, Python, AWS, Time Series Analysis, Api Development, Sql, Git, Pandas, MLops, Gcp, Azure, Large Language Models, LangChain, Generative AI, LLMOps, Scikit-learn, Dataiku, LlamaIndex, ETL workflows

Hadoop, Sql, Deep Learning, Tensorflow, MLops, Pytorch, Gcp, Docker, Spark, Keras, Azure, Kubernetes, Python, AWS, LangChain, DSPy

Spark, Sql, Keras, Natural Language Processing, Tensorflow, Hadoop, MLops, AWS, Pytorch, Python, Kubernetes, Azure, Docker, Gcp, LangChain, DSPy

prophet , causal inference , Sql, Databricks, Tensorflow, MLops, Pytorch, Python, data pipelines, Airflow, Stan, feature engineering, dbt, scikit-learn, PyMC, hierarchical models, R, Bayesian modeling, Experimental Design

Deep Learning, Github, Pandas, Numpy, MLops, AWS, Python, Scipy, Azure, Gcp, Git, Learning-to-Rank, Semantic Retrieval, Personalization Models, Search Relevance Techniques, Generative AI

MLops, Pytorch, Weakly-supervised learning, Deep learning workflows, Medical image analysis, Experiment reproducibility, AI development in regulated environments, Multimodal models

Ml, Sql, Python, Data Science, Database Development, Cloud Computing, MLops, Ai, Front-end application engineering