Research Scientist

Cursor - San Francisco, New York - original posting ->
Status
Open
Remote policy
Onsite
Employment type
Full-time
Salary
Not stated
Categories
Engineering, Machine Learning
Source
cursor
First observed
2026-08-19 07:55 UTC
Last seen
2026-08-19 07:55 UTC
Source claims posted
2026-01-27 22:54 UTC
Consecutive misses
0 of 3

What the posting says

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.

#LI-DNI

Quality

Completeness: 65%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #178314 2026-08-19 07:55 UTC
    Published