Your question is Troubleshooting Production ML. 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).
Describe how you troubleshoot performance bottlenecks in production ML models.
Discuss a practical, systematic approach that distinguishes data-loading, preprocessing, model-inference, serialization, and infrastructure bottlenecks. Explain which measurements, profiling tools, offline tests, and production safeguards you would use. Address both latency and model-quality degradation, including how you would validate an optimization before deployment.
