
Multimodal LLM Development Engineer
2 days ago
Job Overview:
FlashIntel is seeking a dedicated Research Engineer to work on cutting-edge AI projects focusing on Multimodal Large Language Models (m-LLMs) and Text-to-Speech (TTS) technologies. This role offers the opportunity to engage in innovative research and development of AI solutions that integrate various data modalities and enhance interactive systems.
- Research Responsibilities
- Conduct R&D activities to develop state-of-the-art m-LLMs and generative AI models for processing and integrating 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.
Key Responsibilities:
- Model Design & Optimization
- 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.
Collaboration & Learning:
- Work closely with cross-functional teams to translate 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.
Required Skills & Qualifications:
- 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.
- Programming Languages: Proficiency in languages such as Python, with experience in frameworks like TensorFlow or PyTorch.
- Algorithm Design & Data Structures: Understanding of relevant techniques for 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.
- Specialized Skills: Experience with TTS systems, familiarity with agentic workflows, and distributed systems and scalable model deployment.
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