Research Scientist
at Cursor.ai
Posted 19 hours ago
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- Not specified
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- United States
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**Research Scientist | Machine Learning, Reinforcement Learning, San Francisco, New York** Drive innovative RL research end-to-end, owning ambiguous problems. Implement, test, and iterate hypotheses, collaborating in a small, talent-dense team. Experience with RL algorithms, PyTorch or TensorFlow, and MLOps a must. PhD or equivalent in relevant field, with a strong record of research achievements. Join us to automate coding and make professional programmers more effective.
Department: Engineering
Team: Machine Learning
Location: San Francisco
Additional Locations: New York
Employment Type: FullTime
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
