Software Engineer, RL Environments

Cursor
San Francisco
Workplace: OnsiteFull timeFunction: Software EngineeringSkills: ["Truth-seeking","Passionate","Creative","Collaborative","Debate","Problem-solving"]

Build the systems that convert real-world and synthetic data into realistic, training-ready environments for reinforcement learning. You’ll develop scalable platforms and “factory” pipelines that turn raw data into high-quality environments, define automated quality standards, and create self-serve APIs and tools to accelerate task/environment creation. Work closely with ML Platform and research teams to translate model capability goals into effective training tasks at high scale.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Cursor
Cursor
7 hours ago

Software Engineer, RL Environments

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live

Job Summary

Build the systems that convert real-world and synthetic data into realistic, training-ready environments for reinforcement learning. You’ll develop scalable platforms and “factory” pipelines that turn raw data into high-quality environments, define automated quality standards, and create self-serve APIs and tools to accelerate task/environment creation. Work closely with ML Platform and research teams to translate model capability goals into effective training tasks at high scale.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering

Key Responsibilities

  • •Build scalable platforms to create complex, realistic, diverse RL environments at scale for end-to-end knowledge-work tasks.
  • •Design an end-to-end factory pipeline that transforms massive raw data into useful, realistic environments.
  • •Define and apply consistent quality standards across vendor, tutor, acquired, and synthetic data sources.
  • •Create self-serve APIs and tooling that accelerate task and environment development for internal teams and external contributors.
  • •Partner with research, platform, and external teams to translate model capability goals into training tasks and environments.

Key Requirements

  • •Strong software engineering fundamentals with experience building data platforms, developer tools, distributed systems, or ML infrastructure.
  • •Ability to turn ambiguous quality standards into concrete, automated checks.
  • •Comfort building repeatable pipelines from messy, heterogeneous data.
  • •Care about model behavior and translating capability goals into tasks and experiments.
  • •Collaborate across disciplines and own open-ended problems end to end.
Experience:Data platformsDeveloper toolsDistributed systemsML infrastructure
Skills:Truth-seekingPassionateCreativeCollaborativeDebateProblem-solving

Company Brief

Cursor
Builds Cursor, an AI-powered development platform and code editor that helps developers write, review, and maintain code using large language models and developer-focused automation tools for enterprise engineering teams.
Industry: Developer Tools
Company Size: Large (251 to 1,000 employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series D
Headquarters: San Francisco, United States
Founded: 2022
Glassdoor
Glassdoor: 3.0
WebsiteLinkedInGlassdoor