Job Description :

Experience :

7-10 years in ML/speech engineering, 2+ years architecting production voice pipelines.

Key Responsibilities :

- Own end-to-end architecture : ASR ? NLU/LLM ? dialogue manager ? TTS ? telephony

- Make build-vs-buy calls on ASR/TTS vendors (Deepgram, Azure Speech, ElevenLabs, or open-source Whisper/Coqui)

- Own latency budget across the pipeline (target sub-1.5s round-trip for live calls)

- Mentor Conversational AI and ML/Voice engineers; own technical hiring bar

Must-Have Technical Qualifications :

- Production experience with at least one ASR engine (Whisper, Deepgram, Google STT, Azure Speech) at scale

- Hands-on experience with LLM-based dialogue systems (function calling, RAG, or fine-tuning)

- Strong grasp of telephony integration : SIP, WebRTC, Twilio/Exotel/Ozonetel or similar

- Experience optimizing for latency and cost simultaneously in a live voice pipeline

- Comfortable working across Hindi/Hinglish and English accent handling for Indian/UAE markets

- Track record of hitting production accuracy benchmarks : 95%+ transcription (WER-based) accuracy and 90%+ intent classification accuracy at scale not just in a demo

- Experience handling dialect variation and code-switching (e.g. Hinglish, Gulf Arabic variants) in production ASR/NLU

- Successfully deployed and managed Voicebots in a production environment.

- Experience handling 5000+ live customer calls per day.

Good-to-Have :

- Prior experience at Amazon Alexa, Microsoft Cortana/Speech, Google Assistant, or a voice-AI startup

- Exposure to Arabic ASR/TTS for UAE market

- 2+ years hands-on with LLMs/Generative AI in a production (not POC) setting.