Multimodal AI Engineer

2 weeks ago

Bengaluru, Karnataka, India beBeeNlp Full time ₹ 1,00,00,000 - ₹ 1,50,00,000
Research and Development Engineer

FlashIntel is seeking a dedicated and innovative Research Engineer with a focus on Multimodal Large Language Models, Text-to-Speech technologies, and agentic workflows.

  • 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.

  • Key Responsibilities:

    Design and conduct experiments to test new algorithms, architectures, and fine-tuning techniques for TTS applications and agentic workflows.

  • Key Responsibilities:

    Stay updated with the latest academic and industry 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 complex NLP tasks, with a focus on TTS and multimodal integration.

  • Model Design & Optimization:

    Optimize models for scalability, efficiency, and deployment in real-world production systems, ensuring seamless interaction between components in agentic workflows.

  • Collaboration & Learning:

    Work closely with cross-functional teams, including product, engineering, and data science, to translate research insights into tangible products that utilize m-LLMs and TTS technologies within agentic workflows.

  • Collaboration & Learning:

    Engage in a culture of learning and innovation, contributing to team knowledge sharing on m-LLMs, TTS, and AI agents.

  • Required Qualifications:

    • Currently 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.

    • Ability to develop and deploy machine learning models in practical environments, with a focus 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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