AI Multimodal Research Scientist

8 hours ago

Solapur, Maharashtra, India beBeeMultimodal Full time ₹ 15,00,000 - ₹ 25,00,000

Role Overview

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We are seeking a highly skilled Research Engineer with expertise in Multimodal Large Language Models (m-LLMs), Text-to-Speech (TTS) technologies, and agentic workflows.

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Key Responsibilities:

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  • Research & Development:\
  • Develop state-of-the-art m-LLMs and generative AI models processing multiple data modalities, including text, audio, and visual inputs.\
  • Design and conduct experiments for new algorithms, architectures, and fine-tuning techniques for TTS applications and agentic workflows.\
  • Stay updated with the latest advancements in m-LLMs, TTS, and AI agents informing ongoing projects.\
  • Model Design & Optimization:\
  • Develop, fine-tune, and evaluate AI models for complex NLP tasks, focusing on TTS and multimodal integration.\
  • Optimize models for scalability, efficiency, and deployment in real-world production systems ensuring seamless interaction between components in agentic workflows.\
  • Experiment with novel methods in model training, domain adaptation, and performance evaluation enhancing naturalness and responsiveness of TTS systems.\
  • Collaboration & Learning:\
  • Work closely with cross-functional teams translating research insights into tangible products utilizing m-LLMs and TTS technologies within agentic workflows.\
  • Engage in a culture of learning and innovation contributing to team knowledge sharing on m-LLMs, TTS, and AI agents.\
  • Collaborate with external research communities potentially contributing to conferences and publications in m-LLMs, TTS, and agentic AI systems.\
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    • Educational Background:\
    • Currently pursuing an advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, NLP, or a closely related field.\
    • Technical Expertise:\
    • Experience or coursework in large language models, deep learning, NLP, and TTS technologies.\
    • Proficiency in programming languages such as Python, with experience in frameworks like TensorFlow or PyTorch.\
    • Understanding of algorithm design, data structures, and model optimization techniques relevant to m-LLMs and TTS systems.\
    • Professional Skills:\
    • Ability to develop and deploy machine learning models in practical environments, focusing on TTS applications and agentic workflows.\
    • Strong analytical and problem-solving skills, with the capacity to work both independently and collaboratively.\
    • Effective written and verbal communication skills for articulating research concepts to diverse audiences.\

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