performance
AI, ML & GenAI interview questions tagged performance, across every topic.
5 questions · 2 unlocked for you
Concepts behind "performance"
The curriculum that explains the ideas these questions test.
Foundational
Latency Budgets and StreamingLLM latency is not a single figure: time-to-first-token (driven by prefill and queueing) and inter-token latency (driven by decode) feel very different to users. Streaming tokens as they generate masks total latency by showing progress right away. Designing to a latency budget means splitting time across retrieval, model, and tools, tracking TTFT and tokens-per-second (not only end-to-end), and applying streaming, caching, and routing to meet it. AI, ML, and GenAI engineer interviews probe it because perceived latency makes or breaks LLM UX.⚙️ System Design for AI in Production
Foundational
The Big-O That Actually MattersBig-O complexity counts most where it actually hurts in real AI systems: dodge accidental O(n^2) (all-pairs comparisons, repeated linear scans), reach for hash maps to get O(1) lookups, and understand that vector search stays approximate exactly because exact nearest-neighbor costs O(n) per query. The useful skill is catching the quadratic trap and the data-structure fix, not naming complexity classes. Applied-AI interviews test it because the gap between O(n) and O(n^2) separates a system that scales from one that topples over.💻 Coding & Engineering Craft