About The Position

We are seeking a Research Science Lead to spearhead our initiatives in Social Intelligence within complex multi-agent ecosystems. In this pivotal leadership role, you will bridge the gap between centrally orchestrated multi-agent systems and social reasoning paradigms within cognitive science. You will direct a portfolio of research focused on enabling autonomous agents to navigate the "coordination bottleneck" through the development of Theory of Mind (ToM), intent modeling, and emergent social behaviors such as cooperation, coordination, negotiation, persuasion, etc. By synthesizing principles from reinforcement learning, game theory and behavioral science, you will lead an experienced team in to make agents capable of sophisticated alignment, ensuring that agents can operate seamlessly—and ethically—within the intricate social fabric of human-centric environments.

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • A PhD in AI, computer science, data science, science/engineering, or related technical fields
  • First-authored or last-authored publications at peer-reviewed conferences, such as ICML, NeurIPS, ICLR, and other similar venues
  • 2+ years experience holding an industry, postdoctoral, faculty, or government researcher position
  • Research background in machine learning, artificial intelligence, computational statistics, or applied mathematics
  • Experience in developing and debugging in Python or similar programming languages

Nice To Haves

  • Research and engineering experience demonstrated via publications, grants, fellowships, patents, open source code
  • Experience collaborating in a team environment on research projects
  • Experience in applying AI systems to solve science and engineering problems

Responsibilities

  • Perform research to advance the state of the art in our multi-agent ecosystem
  • Work with researchers and engineers in a highly collaborative environment to achieve goals and milestones
  • Influence the future of research in frontier modeling with detailed technical reports
  • Work towards long-term goals, while identifying intermediate milestones
  • Influence progress of relevant research communities by producing publications

Benefits

  • bonus
  • equity
  • benefits
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