Applied AI Researcher, Multi-Agent Systems
Core
Designing multi-agent system architectures where multiple agents coordinate to solve problems requiring structured interaction across reasoning processes.
Role type
Applied AI Researcher (Multi-Agent Systems)
Builds
Self-constructing systems and reliable execution of AI systems for enterprise partners
Domain
Enterprise AI, Multi-Agent Systems, Reinforcement Learning
Deliverable
production ML models
Required skills
Multi-agent system design, agent orchestration, communication protocols, multi-agent reinforcement learning (MARL), graph neural networks (GNNs), knowledge graphs, mixed-initiative planning, prototyping, data analysis
Preferred skills
Published research in top journals, daily usage of generative AI tools (ChatGPT, Cursor, Perplexity)
Technologies
LLMs, agent frameworks, graph databases
Responsibilities
Design architectures for multi-agent coordination, investigate interaction patterns for agent collaboration, build prototypes to prove idea effectiveness, conduct experiments to validate system performance
Seniority
Senior, hands-on IC