Cognitive AI Curriculum Designer

Summary

Aigo.ai is pioneering Cognitive AI technology and is looking for a Cognitive AI Curriculum Designer. The role involves designing curricula to teach AI systems to understand concepts through grounded examples and cognitive stages, working closely with engineering teams to iterate on the system's learning process.

Responsibilities

• Designing and building curricula tailored to the AI’s specific cognitive needs at each stage of development, from early language acquisition through abstract reasoning and theory of mind
• Figuring out how the system could learn something cognitively rather than by hardcoded rule, and what prerequisites it needs to get there
• Identifying and co-developing new cognitive skills required to expand the system’s capabilities
• Creating question/answer sets, comprehension exercises, and structured conversations that challenge and expand the system’s current capabilities
• Identifying gaps and failure modes, then working with engineers to address them in rapid iteration cycles
• Independent research and brainstorming to develop new approaches to curriculum design and capability evaluation
• Evaluating natural language understanding across a wide range of domains, reasoning types, and cognitive tasks
• Designing knowledge ontologies to bolster the system’s fundamental understanding

Skills

• Background in education, cognitive science, linguistics, or a related field, with an emphasis on education
• Deep fascination with the nature of intelligence, language, and how minds (human or artificial) actually work
• Strong command of English and exceptional analytical and writing skills
• Ability to think rigorously and independently, designing tests and curricula from first principles rather than templates
• Comfortable working closely with engineers and iterating quickly in a fast-moving development environment
• Comfortable in a technical environment. You'll spend real time in the system's logs and working out why it did what it did, forming hypotheses about which mechanism failed, and building reproducible cases for engineers. It isn't coding, but it isn't non-technical either
• Familiarity with current AI systems including LLMs is a plus; understanding their capabilities and limitations firsthand is directly relevant
• Multilingual ability is a plus

Qualifications

Must Haves

• Background in education, cognitive science, linguistics, or a related field, with an emphasis on education
• Deep fascination with the nature of intelligence, language, and how minds (human or artificial) actually work
• Strong command of English and exceptional analytical and writing skills
• Ability to think rigorously and independently, designing tests and curricula from first principles rather than templates
• Comfortable working closely with engineers and iterating quickly in a fast-moving development environment
• Comfortable in a technical environment. You'll spend real time in the system's logs and working out why it did what it did, forming hypotheses about which mechanism failed, and building reproducible cases for engineers. It isn't coding, but it isn't non-technical either

Nice to Haves

• Familiarity with current AI systems including LLMs is a plus; understanding their capabilities and limitations firsthand is directly relevant
• Multilingual ability is a plus

Benefits

• Financial compensation of this core team leans more towards meaningful stock options than maximizing cash. Think early Google or SpaceX, employee #15.