Startups · AI

Research Scientist

Engram · San Francisco · On-site

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About Engram

Engram builds AI models that learn from your context and deeply understand your work. Backed by General Catalyst, Kleiner Perkins and Sequoia.

About the role

You will join a small, focused team of researchers and engineers working at the frontier of learning and memory. As a Research Scientist, you’ll design experiments, develop new recipes, build evals, and shape the product used by some of the world's leading tech and AI companies.

What they're looking for

  • Experience bridging research and product — shipping things that real users interact with
  • Familiarity with LLM training infrastructure
  • Engram is based in San Francisco. This role is in-person in our SF office. We offer competitive cash compensation and startup equity
More about this role

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.

You will join a small, focused team of researchers and engineers working at the frontier of learning and memory. As a Research Scientist, you’ll design experiments, develop new recipes, build evals, and shape the product used...

Read the full posting on Engram's site ↗

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