Docker, Azure, Kubernetes, Python, Google Cloud, AWS, R, Machine Learning Operations

Cloud platforms (Azure preferred), Lakehouse architectures (Databricks), Large Language Models (LLMs), Apache Spark, Sql, Tensorflow, Pytorch, Python, Machine Learning Algorithms, MLflow, MLOps practices, Prompt engineering, GenAI application development, Vector databases, Model versioning, Monitoring and drift detection, Agentic AI workflows, Multi-LLM orchestration systems, Statistical Modeling, Distributed computing frameworks, Deep learning frameworks, Embedding models, Automated retraining, CI/CD for ML, Semantic search architectures