RAG pipelines, Agentic AI, Python 3.x, multi-agent systems orchestration, ML GenAI models, Responsible AI practices

Ml, Nlp, MLops, Python, Deep Learning, ranking, Forecasting, Classification, LLM-based applications, Model packaging, anomaly detection

Java, Rest Assured, Kibana, Amazon Web Services, Google Cloud Platform, Soap, JIRA, Sql, Nosql, TestNG, Stash, Git, Jmeter, Mockito, JUnit, Confluence, Bitbucket, Selenium, Postman, Azure, Cloud application development, Podam

Tensorflow, Time Series Analysis, Pytorch, image processing techniques, Forecasting, reinforcement learning, computer vision algorithms

BigQuery, Cloud Storage, tool integration, embeddings, Prompt engineering, Agent loops, Agentic AI Basics, memory fundamentals, Coding Proficiency in Python, Pub Sub, GenAI Basics, Vertex AI, simple RAG concepts, GCP Services, familiarity with APIs and SDKs

Python Programming, Tensorflow, Pytorch, XGBoost, Software Engineering Architecture, Scikit-learn, Production Deployment DevOps, Data Science Analytics, ML DL Frameworks, AI Model Implementation, Cloud Platforms Services, Large Data Processing, API Development Integration, Security Compliance Practices

MLops, Python, AWS, NLP systems, multi-agent systems, cloud-based AI deployments, Llm, RAG, AI frameworks

bedrock , Tensorflow, Lambda, Pytorch, MLops, Docker, ECS, XGBoost, Kubernetes, Python, AWS, Airflow, scikit-learn, Hugging Face Transformers, LightGBM, MLflow, EKS, SageMaker, Kubeflow

RAG, Python programming language, AWS AI ML services ecosystem, FAST APIs, Machine Learning architectures

Pandas, Sql, Tensorflow, Numpy, MLops, Pytorch, Python, Docker, Apis, Nlp, Git, scikit-learn, ETL processes