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Software Engineer, RL Data

Cursor (Anysphere) · San Francisco

Job information is sourced from publicly available employer career pages. Always verify details on the employer's official website before applying.

Why this job?

Discovery score 42/100, built only from evidence stored with this listing.

42/100 discovery
  • New official employer listing

Score components

  • Recency (moves as the posting ages)+18
  • Official employer source+15
  • Rare role+1
  • Company source health+8

Not present on this posting: Salary disclosed、Remote position、Visa sponsorship mentioned、Relocation mentioned、Not found on monitored job boards.

Reasons come from the employer's own posting and our verified source checks. Nothing here is inferred beyond those stored signals.

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. Software Engineer, Reinforcement learning • SpaceXAI is building the future of coding. We train frontier coding agents and scale RL on real user data to make them increasingly effective.

Responsibilities

• As a Software Engineer on the RL Data team at SpaceXAI, 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.

• 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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