SpaceXAI is seeking an AI Humanities Specialist to enhance its models by providing high‑quality data annotations and inputs tailored to humanities contexts. Leveraging expertise in linguistics, history, classical studies, literature, and related fields, the specialist will evaluate model outputs, create training datasets, and collaborate with engineering teams to strengthen the AI’s reasoning and communication.
AI Tutor - Humanities na xAI
Remoto - Remote International
Ver mais vagas na xAISalary
USD 35 - 75
Requirements
Skills
- Deep knowledge in at least one of the following: linguistics, history, classical studies, literature, poetry, philosophy, ethics, visual arts, or performing arts
- Ability to assess arguments for validity, soundness, hidden premises, and category errors, not only for surface correctness
- Habitual reliance on primary sources, with skill at weighing them against secondary literature
- Ability to steel‑man opposing views and separate settled knowledge from interpretation or speculation
- Excellent analytical writing in English: clear, precise, and calibrated to the strength of the evidence
- Comfort working from evolving instructions to produce annotations, critiques, and reference answers at a consistently high standard
- PhD in one of the listed fields, or equivalent demonstrated scholarly depth
- Published analytical work, such as peer‑reviewed articles, monographs, critical editions, catalog essays, or other rigorously sourced scholarship
- Experience in teaching, academic peer review, archival research, textual criticism, historiography, or formal argument analysis
- Range across more than one listed field, or across historically and culturally distinct canons within a field
- Familiarity with evaluating AI or LLM outputs, building benchmarks, or creating training data
- Public writing or lectures that make difficult humanistic material accurate without flattening it
Responsibilities
- Evaluate model outputs in your field for factual accuracy, logical coherence, fallacious reasoning, and hidden assumptions
- Flag confident‑sounding errors, anachronism, misused sources, ideological slant, and claims that outrun the evidence
- Create exemplary responses and datasets that show intellectual honesty, careful source evaluation, and a clear distinction between primary evidence, secondary interpretation, and speculation
- Steel‑man opposing views before criticizing them, and mark what is settled, contested, or unknown
- Ground annotations and reference answers in primary sources whenever they exist, then weigh secondary scholarship against that record
- Collaborate with engineering teams to design evaluation tasks, rubrics, and examples that test and strengthen Grok’s behavior and personality in the humanities
- Help define what good model behavior looks like in contested humanistic questions: precise, sourced, proportionately confident, and resistant to fashionable or motivated readings
Technologies
GrokLLM
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