# Software Engineer, RL Data at Anysphere

- Company: Anysphere
- Role group: Engineering
- Location: San Francisco
- Type: FullTime
- Remote: no
- Posted: 2026-08-27
- Status: active
- Apply: https://jobs.ashbyhq.com/cursor/9a175381-45e2-42b6-bd64-6c84532365f9?ref=companies-hiring.click

## 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.


SOFTWARE ENGINEER, REINFORCEMENT LEARNING

Cursor is building the future of coding. We train frontier coding agents https://cursor.com/blog/composer 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.
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