Multimodal AI Research Specialist

2 days ago

India beBeeResearch Full time US$ 1,20,000 - US$ 1,50,000

Job Opportunity

We are seeking a skilled Research Engineer to join our team in developing cutting-edge AI solutions that integrate various data modalities and enhance interactive systems.

This role offers a unique chance to engage in research and development of state-of-the-art Multimodal Large Language Models (m-LLMs) and generative AI models that process and integrate multiple data modalities, including text, audio, and visual inputs.

Key Responsibilities:

  • Develop novel m-LLMs and generative AI models for complex NLP tasks with a focus on TTS and multimodal integration.
  • Design and conduct experiments to test 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 to inform ongoing projects.

Model Design & Optimization:

  • Participate in developing, fine-tuning, and evaluating AI models for real-world production systems, ensuring seamless interaction between components in agentic workflows.
  • Optimize models for scalability, efficiency, and deployment in production systems, focusing on naturalness and responsiveness of TTS systems.
  • Experiment with novel methods in model training, domain adaptation, and performance evaluation to enhance TTS systems.

Collaboration & Learning:

  • Work closely with cross-functional teams to translate research insights into tangible products that utilize 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 the fields of m-LLMs, TTS, and agentic AI systems.

Requirements:

  • Educational Background: 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.

Preferred Qualifications:

  • Advanced Research Experience: Progress toward a Ph.D. in a relevant discipline with a record of publications or patents.
  • Experience in pioneering research in AI, with familiarity in m-LLM frameworks and toolkits.
  • Specialized Skills: Experience with TTS systems, including speech synthesis and voice conversion technologies.

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