AI Research Scientist

As an AI Architect at Mobius, you will be responsible for designing architectures for meta-learning, self-reflective agents, and recursive optimization loops. Your role will involve building simulation frameworks grounded in Bayesian dynamics, attractor theory, and teleo-dynamics. Additionally, you will develop systems that integrate graph rewriting, knowledge representation, and neurosymbolic reasoning. Your tasks will also include conducting research on fractal intelligence structures, swarm-based agent coordination, and autopoietic systems. Furthermore, you will contribute to advancing Mobius's knowledge graph with ontologies supporting logic, agency, and emergent semantics. You will integrate logic into distributed, policy-scoped decision graphs aligned with business and ethical constraints. It will also be expected of you to publish cutting-edge results and mentor contributors in reflective system design and emergent AI theory. Lastly, you will build scalable simulations of multi-agent, goal-directed, and adaptive ecosystems within the Mobius runtime. **Key Responsibilities:** - Design architectures for meta-learning, self-reflective agents, and recursive optimization loops. - Build simulation frameworks grounded in Bayesian dynamics, attractor theory, and teleo-dynamics. - Develop systems integrating graph rewriting, knowledge representation, and neurosymbolic reasoning. - Conduct research on fractal intelligence structures, swarm-based agent coordination, and autopoietic systems. - Advance Mobius's knowledge graph with ontologies supporting logic, agency, and emergent semantics. - Integrate logic into distributed, policy-scoped decision graphs aligned with business and ethical constraints. - Publish cutting-edge results and mentor contributors in reflective system design and emergent AI theory. - Build scalable simulations of multi-agent, goal-directed, and adaptive ecosystems within the Mobius runtime. **Qualification Required:** - Proven expertise in meta-learning, recursive architectures, and AI safety. - Experience in distributed systems, multi-agent environments, and decentralized coordination. - Strong implementation skills in Python (required), with additional proficiency in C++, functional or symbolic languages being a plus. - Publication record in areas intersecting AI research, complexity science, and/or emergent systems.,