# Learning Scientist

**Company:** [AI Fund](https://hotfix.jobs/companies/ai-fund)
**Location:** Mountain View, CA
**Role:** AI Research
**Skills:** Learning Science, Experimental Design, Statistics, Python, R, Human Subjects Research, Psychometrics, Assessment Validity, Item Response Theory, Rubric Calibration, Rater Reliability, Intelligent Tutoring Systems, Adaptive Learning, Artificial Intelligence
**Posted:** 2026-08-12

> Designs AI-native teaching methods and establishes rigorous measurement of skill gain, retention, and transfer. The role requires deep learning-science knowledge, strong experimental and statistical skills, human-subjects research experience, and technical fluency with Python or R.

## Job Description

## Responsibilities
- Invent and prototype AI-native teaching methods with engineers and integrate them into the product.
- Design the measurement framework for skill gain, retention, and transfer, including product instrumentation.
- Run well-designed studies with real learners, from short pilots to longitudinal cohorts.
- Build trustworthy performance assessments and rubrics, treating validity and reliability as engineering requirements.
- Establish an evidence-based standard for pedagogical decisions across the company.
- Partner directly with the founding team to guide product and instructional decisions with research findings.

## Requirements
- Deep knowledge of learning science and research on retrieval, spacing, feedback, transfer, and expertise development.
- Strong experimental-design and statistical skills, including study power and signal-versus-noise evaluation.
- Human-subjects research experience in laboratory or field settings.
- Technical fluency with Python or R and ability to collaborate with engineers on instrumentation.
- Excellent communication skills for making evidence actionable to non-specialists.

## Nice-to-haves
- PhD in learning sciences, cognitive psychology, education, or a related field, or equivalent research experience.
- Experience with intelligent tutoring systems, adaptive learning, or AI-based instruction.
- Psychometrics and assessment-validity experience, including IRT, rubric calibration, and rater reliability.
- Experience measuring learning in adult professional or workplace contexts.

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