Your question is Balancing Complexity and Latency. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How do you balance model complexity with latency requirements when designing real-time inference pipelines?
Discuss how you would decompose the pipeline, measure latency, and choose models for each stage. Cover optimization techniques, online versus batch computation, capacity planning, fallbacks, and monitoring for quality, drift, and training-serving skew.
