containerization , MLops, Distributed Systems, Logging, LLM-based systems, Alerting, Model observability, Vector databases, Drift detection, Scalable inference systems, Machine Learning Engineering, Orchestration patterns, Model training, Cloud-native architectures, Embeddings, Data ingestion, Experiment tracking, cost tracking, ML platform development, tracing, Feature management, Model registry, Monitoring

FastAPI, Pyspark, Sql, Tensorflow, Azure ML, Pandas, Pytorch, XGBoost, Flask, Databricks, Python, Azure DevOps, scikit-learn, LightGBM

Sql, Machine Learning, Gcp, Docker, Spark, Kafka, Kubernetes, Python, AWS, RAG, Generative AI models, Llm

Scipy, Tensorflow, Machine Learning, Nlp, Pytorch, Keras, Python, Deep Learning, scikit-learn, LLMs Tools, Data Analysis Techniques