Sarvam AI MLE Interview Questions (2026)

Questions reported from Sarvam AI machine learning engineer interviews. This bank tracks 8 questions asked at Sarvam AI (6 with free model answers). Practice them live with DeepOffer's AI voice interviewer.

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#47 Describe how byte-pair encoding works and where it breaks down (numbers, code, non-Latin scripts). ★
#72 Explain why tokenization is the first bottleneck for Indian-language LLMs and how a low-fertility tokenizer changes the economics.
#88 Compare LoRA, prefix tuning, prompt tuning, and full fine-tuning, and state when each is the right choice. ★
#92 Explain RLVR and where it beats a learned reward model. ★
#157 Explain how to build ASR that handles code-mixed speech such as Hinglish, given Whisper's failures there. ★
#158 Explain the hard parts of text normalization and prosody for code-mixed, mixed-script TTS. ★
#204 Budget latency for a real-time voice agent across VAD, ASR, LLM, TTS, and network, and say where the time goes. ★
#231 Design cross-lingual RAG where the knowledge base is English and Hindi but users ask in Tamil, Telugu, or transliterated Hinglish.