Data Management, Pyspark, Sql, Machine Learning Algorithms, Statistical Analysis, Python, Open-Source Programming Languages, MLOps pipeline management, Multi-cloud architecture, DevSecOps practices, AI ML architectures, Governance, Advanced frameworks, Analytics, Artificial Intelligence Systems, System design principles, Experimental Design, Cloud Development, Feature engineering techniques, Business Intelligence

Cloud Computing, Machine Learning, Data Visualization, Big Data, Python, Sql, Statistical Analysis, Deep Learning

data preparation , Text Analytics, Tensorflow, Deep Learning, Numpy, Nlp, Nltk, Pytorch, Excel, Python, Power Bi, Sql, Pandas, Spark, Databricks, knowledge graphs, pgvector, scikit-learn, vector databases, evaluation frameworks, Streamlit, RAG pipelines, responsible AI practices, SpaCy, LLMs, prompt engineering, Agentic AI, FAISS

Computer Vision, Python, Version Control, Testing, MLops, Azure cloud experience, Natural Language Understanding, agentic AI principles, generative AI

Sql, Tensorflow, Tableau, Deep Learning, MLops, Power Bi, Pytorch, Python, Nlp, R, cloud platforms, big data tools, ML frameworks

, Sql, Deep Learning, AWS, Pytorch, Data Manipulation, Python, Azure, Gcp, Big Data, Speech NLP, Statistics, experimentation, GPU Computing, Modeling, Generative AI

Sql, Tensorflow, Machine Learning, Python, Scikit-Learn

Statistical Analysis, Machine Learning, Predictive Modeling, Python, Sql, R

Tensorflow, MLops, Pytorch, Spark, Data Privacy, Kubernetes, Python, LangChain, MLflow, Pinecone, AI compliance standards, OpenAI APIs, FAISS, LlamaIndex, CI CD for ML