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Tier-1 funded metro role increases applicants, while speech/Indian-context specialization narrows the pool.
Specialized ASR/TTS, multilingual and agentic LLM expertise limits straightforward cross-industry transferability.
Explicit 4+ years and mandatory ASR/TTS, LLM, low-latency production and framework skills create strict filters.
Design, train, and optimize custom ASR/TTS and multilingual speech models focused on Indian contexts to improve conversational AI accuracy.
Develop and deploy real-time, low-latency, robust conversational agents handling interruptions, pauses, and voice variability.
Build and enhance voice-to-voice systems, agentic RAG pipelines, and self-learning agents integrated into production environments with MLOps collaboration.
Bachelor’s degree in Computer Science, AI/ML, or related field.
4+ years of hands-on ML engineering experience, particularly in speech or NLP systems.
Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
Experience designing low-latency, real-time ML applications and prior work on multilingual or Indian-context ASR/TTS systems.
Experienced ML engineer specializing in speech and dialogue systems with strong expertise in ASR, TTS, NLP, and LLM fine-tuning.
Proven ability to deploy and maintain scalable, secure, and reliable real-time ML systems in production.
Comfortable working at the intersection of speech technology, large language models, and production-grade AI engineering in an enterprise startup environment.