Backed by Sequoia.
About the role
You will invent new ways to teach that take advantage of agentic AI — and apply rigorous measurement to prove they work. Agentic AI makes teaching moves possible that no classroom or MOOC could offer: a tutor that remembers everything, infinitely patient practice, feedback on real work product, assessment woven invisibly into learning. Most of these possibilities are unexplored, and much of what's shipping across the industry today has no evidence behind it.
What they're looking for
- - 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
More about this role
For most of history, great teaching has been scarce. A brilliant teacher who knows you well, adapts to how you learn, and patiently stays with you until you get there — almost no one has had that. AI changes what's possible. LearnVector, founded by Andrew Ng, is building a trustworthy AI guide for learning, with a mission to accelerate human development. We're a small, fast-moving team working on-site in Mountain View, California and backed by a $100 million investment from Coursera.
You will invent new ways to teach that take advantage of agentic AI — and apply rigorous measurement to prove they work. Agentic AI makes teaching moves possible that no classroom or MOOC could offer: a tutor that remembers everything, infinitely patient practice, feedback on real work product, assessment woven invisibly into learning. Most of these possibilities are unexplored, and much of what's shipping across the industry today has no evidence behind it.
Your job is both halves: design the new methods, and hold them to the standard of evidence. What did the learner retain a week later? Can they apply it to work that looks nothing like the exercise? You'll be the person in the company whose answer...
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