snowflake , Servicenow, Microsoft Azure, Databricks, AWS, Computer Vision, Salesforce, Churn Risk Models, Responsible AI Model Governance, AI ML solution design and architecture

Machine Learning, Ai

data engineering , Machine Learning, Deep Learning, Big Data, Cloud Computing, Python Programming, Api Development, Data Visualization, AI ML, Model Deployment, DevOps Practices

Deep Learning, Tensorflow, Pytorch, Computer Vision, Azure ML, Microservices, AWS, Kubernetes, Python, Docker, Apis, Nlp, Airflow, cloud platforms, scalable system design, large-scale systems, AI ML system design and architecture, data engineering pipelines, MLOps tools, Kubeflow, MLflow, Scikit-learn, SageMaker, GCP AI, generative AI

Ml, APEX, Flows, Mobile Application Development, Ai, agentic systems architecture, AI governance, Gemini, cloud-native architecture, Agentforce custom agent frameworks, Agentforce, AI agents, LLM-based systems, Lightning Web Components, agentic tool-use patterns, automation platforms, Salesforce Field Service solution development, integration patterns, platform scalability principles, Salesforce platform architecture, prompt engineering, responsible AI, AI risk frameworks, LLM orchestration

MLops, LangChain, CrewAI, LLMs, interaction protocols, Planning Modules, LLMOps, action execution frameworks, architectural best practices, AI agent ecosystems, perception interfaces, agent lifecycle management, knowledge integration, AutoGen, memory systems, tool API integration, Google ADK