AI Research Scientist

2 days ago

Salem, Tamil Nadu, India beBeeMachineLearning Full time US$ 1,20,000 - US$ 1,60,000
Research Opportunities

We are seeking a talented Research Engineer to join our team and contribute to cutting-edge projects in multimodal large language models (m-LLMs) and text-to-speech (TTS) technologies.

This role offers a unique opportunity to engage in innovative research and development of AI solutions that integrate various data modalities and enhance interactive systems.

Ideal candidates have a strong passion for AI and natural language processing (NLP), and are eager to contribute to pioneering projects.

Candidates with advanced degrees (Master's or Ph.D.) in relevant fields, such as computer science, machine learning, or NLP, are preferred.

Key Responsibilities
  • Develop state-of-the-art m-LLMs and generative AI models that process and integrate multiple data modalities, including text, audio, and visual inputs.
  • 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.
  • Develop, fine-tune, and evaluate AI models for complex NLP tasks, with a focus 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.
Required Skills and Qualifications
  • Pursuing an advanced degree (Master's or Ph.D.) in Computer Science, Machine Learning, NLP, or a closely related field.
  • 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.
Benefits and Culture
  • A culture of learning and innovation, where team members contribute to knowledge sharing on m-LLMs, TTS, and AI agents.
  • Collaboration with cross-functional teams to translate research insights into tangible products that utilize m-LLMs and TTS technologies within agentic workflows.
  • Opportunities to engage with external research communities and contribute to conferences and publications in the fields of m-LLMs, TTS, and agentic AI systems.

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