System Design — Model Accuracy & AI Performance

Overview

This directory contains 5 full system design walkthroughs for the most common scenarios in a Senior Staff ML engineer interview at Qualcomm and similar companies. Each document follows the standard system design interview format: requirements → high-level design → deep dive → trade-offs → scale considerations.

Scenarios

How to Practice System Design

1. 30 minutes to design: cover requirements, API, data model, core algorithm, scale
2. Never show only happy path: always discuss failure modes, monitoring, rollback
3. Quantify everything: "1000 model evals/day" not "many evals"
4. Know the trade-offs: at Senior Staff level, there is no single right answer — you need to articulate WHY you made each architectural choice
5. Connect to hardware: at Qualcomm, every system design should mention how it handles NPU-specific constraints (static shapes, quantization, HTP fallbacks)

Senior Staff Differentiators

What distinguishes a Senior Staff system design from a Senior:

• Platform thinking: builds the system so other teams can use it, not just your team
• Observability first: metrics, alerts, and debugging are first-class, not afterthoughts
• Policy engine: accuracy regression policy is configurable, not hardcoded thresholds
• Multi-dimensional quality: latency + accuracy + energy + memory simultaneously, not just one axis