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Software Engineer, RL Data

Cursor · San Francisco

Location
San Francisco
Funding
$2.7B
Posted
Aug 27, 2026

Cursor is hiring a Software Engineer, RL Data based in San Francisco. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.

Apply directly at Cursor

Role details

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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