AI & ML
Production Reliability, Safety & Governance
Ship ML systems that work at scale. MLOps, caching, routing, observability, prompt injection defense, and AI governance.
MLOps Fundamentals
ML Pipeline Design
Model Serving Architecture
Monitoring and Observability
ML System Design
Recommendation Systems
Search and Ranking
LLM Application Architecture
Real-time ML Systems
Production LLM Infrastructure
Caching Layers (Prompt, Semantic, KV Cache)
Model/Tool Routing and Fallback Strategies
Observability for LLM/Agent Workflows
Safety & Governance
Bias and Fairness in ML
LLM Safety and Alignment
Responsible AI Practices
Privacy in ML Systems
Environmental Impact
Governance & Documentation
Security & Incident Response
Prompt Injection Defenses
Secure Tool Use (AuthZ, Secret Management)
Incident Response for AI Systems