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Location
In office (San Francisco, New York)
Employment
Full-Time
Overview
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Anysphere builds Cursor, a code editor designed around AI assistance, where the model reads an entire repository and edits across files rather than completing single lines in isolation. Its agent mode plans and carries out multi-step changes, runs commands and reviews its own diffs, which made the editor one of the fastest-growing developer tools of the current AI wave and a standard part of many engineering workflows. The company describes itself as an applied research lab and trains its own models alongside the product.

Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.

Research Scientist

Cursor is building the future of coding. We train frontier coding agents and scale RL on real user data to make them increasingly effective.

About the role

We’re looking for Research Scientists who can drive effective RL or mid-training research in a small-team setting. You’ll own ambiguous, hard research problems end-to-end: forming hypotheses, designing experiments, building the training/eval/data needed to test them, and pushing results into the next model. You should expect significantly more scope and autonomy than in other research labs.

What you’ll do

  • Improve our understanding of RL, what it takes to handle longer horizon tasks, and train with less compute

  • Train graders to improve performance on coding tasks with non-verifiable reward

  • Improve the quality and difficulty of datapoints we use for training our models

  • Realtime RL for coding agents

You may be a fit if

  • You have a deep background in RL and strong machine learning fundamentals

  • You’re an excellent programmer and software engineer

  • You can handle ambiguous research tasks with little guidance

  • You care a lot about data quality, and can dive into the data when appropriate

  • You are truth seeking, aiming to learn more about the science than proving your ideas are correct.

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