The mission in one sentence

Cursor's stated goal is to automate coding. A Research Scientist exists for one reason inside that goal: make the next coding-agent model meaningfully better, primarily through reinforcement learning trained on real user data.

Read this section as the role contract. The diagram or table names the surface area, but the interview signal is whether you can turn it into a clear operating claim: what you own, what you do not own, what evidence proves the work is working and where judgment matters.

That is the whole job in a line. Everything else in the JD is a specialization of it. You are not hired to survey a field, write a position paper or maintain a benchmark. You are hired so that the model shipping to Cursor users a quarter from now is better than the one shipping today and so that you can say why it improved.

The center of gravity is RL, not pretraining and not prompt engineering. The named surface area is concrete.

• Extending RL to longer-horizon agent-assisted tasks - episodes that span many tool-calls, not single completions.
• Compute-efficient training - more capability per FLOP, training at lower cost.
• Graders for non-verifiable rewards - scoring code where unit tests can't fully judge quality.
• Datapoint quality and difficulty - what makes a training example good, hard and representative of real requests.
• Realtime / online RL - learning from live user interactions, as shipped behind Cursor TabCursor's original autocomplete: multi-line, edit-aware suggestions you accept with the Tab key. Press Enter for the full definition..