The 60-second answer
Define relevance and downstream use first: search retrieval, recommendation, spam prevention, or hashtag quality can require different thresholds. Build labels from creator choices plus human review/engagement carefully; encode video frames, ASR/OCR/caption, hashtag text, and contextual metadata.
Build the answer in this order
Define relevance and downstream use first: search retrieval, recommendation, spam prevention, or hashtag quality can require different thresholds.
Build labels from creator choices plus human review/engagement carefully; encode video frames, ASR/OCR/caption, hashtag text, and contextual metadata.
Use dual-encoder retrieval-style similarity or richer cross-modal matching, calibrated per hashtag frequency and language.
Evaluate precision/recall by head/tail hashtag, language/content type, online search/recommendation impact, and abuse/adversarial tagging.
A useful interview mental model
This is the shape of a strong answer—not a script to memorize.
Senior-level signal
- Senior answers discuss popularity bias, weak-label contamination, and tail-hashtag cold start.
- Separate semantic relevance from policy/safety eligibility and monitor both independently.
What the interviewer is really testing
Likely follow-up questions
Common weak-answer patterns
- Jumping to a model before defining the product contract.
- Listing components without bottlenecks, metrics, or failure handling.
- Ignoring data quality, serving latency, monitoring, and iteration.