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Learning Scientist

AI Fund
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Mountain View, CAFull-timePosted 2mo ago

About the role

Learning Scientist role at LearnVector, Mountain View, CA. On-site, full-time. Focus on inventing AI-native teaching methods, designing measurement backbone, and running studies to evaluate learning outcomes with rigorous evidence.

Responsibilities

  • Invent and prototype AI-native teaching methods — working with engineers to build them into the product, not writing papers about what could be built
  • Design the company's measurement backbone: what we measure to know learning happened (skill gain, retention, transfer), and how it's instrumented into the product
  • Run studies with real learners — from one-week pilots to longitudinal cohorts — sized and designed so results mean something; kill designs the evidence doesn't support, including your own
  • Build assessments worth trusting: performance tasks and rubrics that measure real competence, with validity and reliability treated as engineering requirements
  • Set the evidence bar company-wide: when the team debates a pedagogical choice, you bring the literature and the data, and you're open to being wrong
  • Work directly with the founding team, including Andrew, on what we build and what we believe; your evidence shapes decisions at the top, not just recommendations that get filed

Qualifications

  • Deep grounding in learning science — the experimental literature on how people acquire and retain skills (retrieval, spacing, feedback, transfer, expertise development) and where its limits are
  • Strong experimental-design and statistical skills: you know what a well-powered study needs, and you notice when a result is noise dressed as signal
  • Research experience with human subjects — lab or field — and the pragmatism to run informative studies inside a fast-moving product, not just ideal ones
  • Enough technical fluency to work with data directly (Python or R) and to collaborate closely with engineers on instrumentation
  • Excellent communication: you make evidence legible and actionable to a non-specialist team
  • Nice to have: PhD in learning sciences, cognitive psychology, education, or a related field — or equivalent research experience
  • Nice to have: Experience with intelligent tutoring systems, adaptive learning, or AI-based instruction
  • Nice to have: Psychometrics and assessment-validity experience (IRT, rubric calibration, rater reliability)
  • Nice to have: Experience measuring learning in adult professional or workplace contexts, where completion and retention behave nothing like the classroom

Skills

Required:Learning science expertiseExperimental designHuman subjects researchData analysis (Python or R)Communication
Last updated Oct 21, 2026. Interested? Apply on the company site.

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