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Tier-1 employer and metro location increase applicants, but niche LLM and edge specialization moderates competition.
Strong ML/LLM, edge deployment, and speech specialization limits transferability across industries.
Requires specific LLM fine-tuning, quantization, edge deployment skills and Python — strict technical filters.
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Develop and optimize edge-deployable language models (SLM/LLM) with quantization techniques for autonomous and conversational AI systems.
Design and build AI agent frameworks, including multi-agent systems, leveraging LangChain-based APIs and scripting data analysis and model evaluation pipelines.
Drive innovation through research and application in applied AI/ML focusing on autonomous systems, conversational agents, and potentially voice AI technologies.
Strong proficiency in Python programming.
Minimum 1-2 years hands-on experience in fine-tuning Large and Small Language Models.
Demonstrated expertise in quantizing and deploying optimized language models on edge or embedded devices.
B.Tech or M.Tech degree.
Experience with AI agent framework design and development, especially using LangChain-based APIs.
Background in NLP with proven hands-on development of advanced conversational agents.
Research-oriented candidate with published papers in reputed AI/ML conferences and experience handling Indian languages or speech technologies (ASR/STT, TTS, Intent/Entity extraction) is strongly preferred.