Research Scientist

Cursor; New York, San Francisco (NY, CA); On-site; USD 100,000 - 130,000; Full time

Job summary

cursor is hiring a Research Scientist to drive research in reinforcement learning at their New York office. Candidates should have a deep background in RL, be excellent programmers, and be comfortable handling ambiguous tasks with minimal guidance.

The role involves enhancing the understanding of RL, improving data quality for model training, and executing realtime RL for coding agents. This position offers significant scope and autonomy within a small, talented team.

Qualifications

• Deep background in Reinforcement Learning.
• Excellent programming and software engineering skills.
• Ability to handle ambiguous research tasks with minimal guidance.

Responsibilities

• Improve understanding of RL for longer horizon tasks.
• Train graders to enhance performance on coding tasks.
• Improve data points quality for training models.
• Implement realtime RL for coding agents.

Skills

Reinforcement Learning

Programming Skills

Machine Learning Fundamentals

Data Quality Focus

Job description

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.