engram

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Older posting · still listed ·

  • onsite
  • FullTime
  • Future Opportunities
  • San Francisco
Work arrangement
onsite
Employment
FullTime
Stated compensation
Not specified
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Requirements

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Remote policy
onsite
“Provider workplace type: onsite”
From employer posting metadata
Employment type
FullTime
9 fields not stated in this posting
Employer sponsorship
Not specified
Geographic scope
Not specified
Degree requirement
Not specified
Security clearance
Not mentioned
Timezone / hours
Not specified
Citizenship requirement
Not mentioned
Minimum experience (years)
Not specified
Work authorization
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Compensation
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READ IT IN THE EMPLOYER’S OWN WORDS

Original job description

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About 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.
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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. If you’re interested in working with us, but don't see an open role that matches your skillset, we'd still like to hear from you! Filling out this form lets us know you're open to hearing from us down the road about roles or opportunities that might be a great fit for you.
Original formatting and links

About 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.

If you’re interested in working with us, but don't see an open role that matches your skillset, we'd still like to hear from you! Filling out this form lets us know you're open to hearing from us down the road about roles or opportunities that might be a great fit for you.

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