About this role
Role Overview
Create reproducible reinforcement learning environments that evaluate an AI model''s ability to complete complex software engineering workflows. The work reflects real DevOps, CI/CD, debugging, and command-line workflows using tools such as Git, Docker, GDB, ASan, and FFmpeg, and includes a golden reference solution for each environment.
Key Responsibilities
- Contribute production-quality code, reviews, and documentation to relevant open-source repositories.
- Design, implement, and optimize complex algorithms and system components in C++, Python, Java, Go, TypeScript, or Rust.
- Identify and resolve technical issues, bugs, and performance bottlenecks in existing codebases.
- Collaborate with contributors and stakeholders to align deliverables with project goals and engineering best practices.
- Create, maintain, and improve technical documentation that supports knowledge sharing and onboarding.
- Participate in code discussions and provide constructive feedback to improve code quality.
Qualifications
- Demonstrable open-source contributions and a public GitHub or GitLab profile.
- Working knowledge of Python 3, Java, Rust, C++, TypeScript, or Go.
- Experience with large-scale, distributed codebases is preferred.
- Experience participating in rigorous code reviews and helping establish software best practices is preferred.
- Familiarity with modern AI or machine learning systems is helpful but not required.
Work Terms
- Remote, independent contractor engagement.
- Work is output-based, with payment tied to tasks that meet project specifications. Completion time may vary based on experience and workflow.
- Minimum submission requirements apply, including a required minimum number of tasks each week.
- Selected contributors should be ready to begin promptly, with first tasks expected within 24 to 48 hours after completing the required setup process. Roles are commonly filled within 48 hours.
Compensation
Advertised compensation is $50 to $150 per hour. Payment is made per qualifying task that meets project specifications.
Application Process
- Submit an application and complete the screening questions.
- Complete an approximately 30-minute AI interview.
- Complete a technical assessment if requested.
- Your application will then be reviewed by the hiring manager.