How the interviewer opens it
“Design a system that generates time-aligned captions for uploaded videos. It must support multiple languages and noisy audio while keeping processing time manageable.”
The prompt is vague on purpose. The first minutes are for you. Reduce the prompt to the core features and agree on the numbers before you draw.
What to clarify first
- Workload
- Read and write mix
- Languages
- Caption quality
- Latency
- Consistency and durability
- Access and retention
- Media and time
- Invalid media and absent speech
- Scope boundaries
The interviewer has the answers. In a SysRound round, Alex gives these answers, as a real interviewer does.
Scope of a strong answer
Core requirements
- Generate captions for speech in the source language
- Create one translated track when the user requests it
- Keep caption times aligned with the video
- Report job status and return caption files
Usually out of scope
- Live captions
- Model training
- Video playback infrastructure
- Human review services
What interviewers ask about
- Caption times
- Audio transforms, parallel work, and translation can each break the relationship between caption times and the original video clock.
- Speech quality across languages
- Noise and language changes produce different errors. A single average accuracy score can hide poor results for one language.
- Completion time under load
- Job counts hide large differences in audio work. Queue delays can consume the latency budget before a model starts.
- Repeated requests and failures
- Retries can repeat work. Zone failures can lose accepted jobs or expose incomplete captions unless each storage step has a clear durability contract.
Common mistakes
- Runs the full caption job inside the upload request.
- Estimates capacity from video counts instead of audio duration.
- Divides audio without preserving source times or resolving boundary errors.
- Treats translation as direct speech recognition in the target language.
- Promises accurate text for unclear speech without uncertainty or language-specific evaluation.
- Ignores duplicate work, stale workers, partial caption files, or durability across zones.
The bar by level
- Senior (L5/E5)
- Explains boundary reconciliation, language quality checks, and safe publication. Budgets queue and model time. Handles duplicate work and specifies storage behavior during zone failure.
- Staff (L6+/E6+)
- Defines measurable quality and latency contracts. Balances model choice, fleet cost, and fairness. Specifies acceptance limits, revision ownership, and recovery across storage boundaries.