You need an assistant that serves users writing in Hindi, Tamil and mixed Hinglish. What prompting and evaluation challenges do you expect?
What the interviewer wants to hear
- Model quality differs by language; test each one
- Code-mixed and transliterated input
- Instructions about reply language and script
- Native-speaker evaluation and rubrics per language
- Higher token usage and cost for some scripts
Model answer
Model quality is not equal across languages, so I would evaluate each one separately rather than assuming English results carry over. Users often mix languages and write Hindi or Tamil in Roman letters, so the eval set must include code-mixed and transliterated inputs from real users. The prompt needs clear rules on reply language and script, for example "reply in the same language and script the user writes in", and what to do for mixed input. Cultural tone and formality matter too. Evaluation needs native speakers, with rubrics for fluency, correctness and naturalness, since an LLM judge may be weaker in those languages; I would calibrate any judge per language. Non-Latin scripts can use more tokens per word, raising cost and latency, so I would measure token usage per language and keep prompts concise.
Can you answer it under time pressure?
Take a timed hard round and get scored on every answer.
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