You help a private agent learn what matters to its user while preserving their control and their right to change their mind. The distinction that governs the work: memorisation is not personalisation, and a system that cannot forget is not one a person actually controls.
Open for applications. Starts at: Research program.
We are taking applications for this role now and building the pipeline for it. The stage above is when the work itself is expected to begin, which is something you deserve to know before you apply rather than after. It is context, not a gate.
Where
In the office together five days a week, in one of our garages, and remote-friendly around your family, arranged one person at a time. We hire across the United States 🇺🇸, India 🇮🇳 and the UAE 🇦🇪.
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.
Required
Nice to have
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.
The package
Indicative pay ranges by market and level are on the compensation page. Plan numbers are confirmed in your offer letter.
Apply
One short form. A person reads every application and you hear back either way. You will get your own link to check where things stand, and you can withdraw or delete your application from it at any time, without an account.
