Software Engineer, RL Data
at Cursor.ai
Posted 18 hours ago
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- Not specified
- City
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- United States
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**Software Engineer, RL Data** Lêad the RL Data team at Cursor, designing tasks, rewards, and environments for training coding agents. Develop and manage real user data pipelines, ensuring high-quality data for model training. Key responsibilities include task creation, reward function design, and environment setup. Collaborate with cross-functional teams to define agent capabilities and measure model performance. Required skills: Python, RL algorithms, TensorFlow, PyTorch, and familiarity with RL platforms like RLlib or Stable Baselines. 3+ years of experience in reinforcement learning or a related field.
Department: Engineering
Team: Machine Learning
Location: San Francisco
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.
Software Engineer, Reinforcement learning
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
As a Software Engineer on the RL Data team at Cursor, you'll create the tasks, rewards, and environments that train our coding agents. The team owns the data that goes into training: what the model is asked to do, how we score it, and the setups it learns in.
What you’ll do
Designing a task set that teaches a specific agent capability, then iterating on it from traces and evals until the model actually gets better.
Reading a pile of agent traces, finding a failure mode or a surprising behavior, and building a system that surfaces more of the same.
Turning a one-off recipe into something other teams can reuse: better rewards, cleaner environments, tighter data quality.
Partnering with research on whether a dataset is actually teaching the thing we think it is.
You may be a fit if
You write careful, fast code and have strong software engineering fundamentals.
You like setting tasks: breaking a fuzzy capability into something concrete you can measure.
You have an infra, data, or distributed systems background. RL experience is a plus, not a requirement.
You enjoy looking at messy real-world agent behavior and turning it into a dataset or a tool.
