Roles & Responsibilities:
- Advanced Model Development: Lead the design and implementation of advanced Generative AI solutions, including LLMs, GANs, VAEs, Diffusion Models, and multi-modal systems.
- Optimize models for deployment in multi-agent settings, ensuring agent-level scalability and robustness.
- Multi-Agent System Design: Architect and deploy multi-agent systems, enabling AI agents to collaborate, share knowledge, and solve tasks dynamically.
- Develop frameworks for agents to interact effectively using generative AI for reasoning, task execution, and learning.
- Production Deployment: Manage and oversee the deployment of at least one Generative AI model or multi-agent system in production, ensuring operational excellence and high availability.
- Strategic Leadership: Collaborate with stakeholders to identify opportunities for Generative AI and multi-agent systems, define use cases, and create actionable strategies for implementation.
- Drive thought leadership in multi-agent architectures and Generative AI innovation.
- Mentorship: Mentor junior team members in building and deploying Generative AI models and multi-agent systems.
- Research and Development: Drive internal research initiatives and contribute to the AI community through papers, patents, or open-source projects in Generative AI and multi-agent systems.
Essential Skills:
- 10+ years of experience
- Advanced knowledge of multi-agent design principles, agent-based simulations, and reinforcement learning for multi-agent systems.
- Expertise in transformers, GANs, VAEs, and Diffusion Models.
- Experience with tools like Ray, DeepSpeed, and cloud-based deployment pipelines.
- Strong grasp of optimization techniques like quantization, pruning, and knowledge distillation
Education Qualifications: Bachelor’s degree in Engineering ( Computer Science/Information Technology)