Help a private agent learn what matters to its user while preserving control and the ability to change their mind.
Not open yet: Research program
This work starts when that stage arrives, so there is no application to submit today and we will not pretend otherwise. What is written below is what the role is for and what would make somebody right for it, published early on purpose so you can decide whether it is worth watching.
The work
Research adaptation, memory selection, preference learning and resistance to forgetting or poisoning. Compare retrieval, explicit settings and parameter updates rather than assuming training is always necessary. Test what can be removed from memory and what model-level removal can actually guarantee.
The milestone
In your first 90 days, deliver a personalization experiment with held-out evaluation, rollback and documented deletion limitations.
Evidence
Bring machine-learning research expertise and careful reasoning about privacy, causality and evaluation. Show work that distinguishes memorization from useful generalization.
Evidence, not credentials. We are describing work you can point at, in whatever form it exists.
The exercise
Design an experiment where a user's preferences change and the system must update without exposing another household member's data.