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Similar roles pay $115K - 155K a year · our estimate
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Sign Up to ReadAbout Engram
Today’s AI is a brilliant stranger: it can solve the world’s hardest math problems, but it knows next to nothing about you and your work. It rereads your files to answer even basic questions, burns an enormous amount of tokens when sifting through large corpuses, and between sessions, it retains scraps at best.
We train models to study your world and anticipate your questions in advance, forming engrams: compact memories that capture your knowledge and history. Our approach opens a new axis of scaling. The more we study your context at training time, the better we become at inference time.
We're already working with leaders in AI like Microsoft, Notion, and Harvey, and just raised $98M from General Catalyst, Kleiner Perkins, Sequoia, Factory, Modern, Amplify, Neo and others. Our investors and advisors include Assaf Rappaport, Andrej Karpathy, and Pieter Abbeel.
AI has spent years learning everything about the world. Now it should learn something about yours.
About the role
Every Engram customer gets models trained on their own context, such as their documents, messages, code, and knowledge bases, and retrained continuously as that context changes. That means isolation can't stop at where data is stored: it has to follow the data into training runs and into the models themselves.
We're looking for an infrastructure engineer to own and evolve the systems that make that true, from ingestion through training to inference, as we add customers and providers. You'll work closely with our researchers so the secure path is also the fast one.
From the office
Engram
Office in San Francisco, United States
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$231,000 - 318,000 / year
Salary by agreement