In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

As an expert you will be creating Reinforcement Learning Environments which test and AI model's ability to solve complex software engineering problems related to fixing code, creating features, refactoring code and optimizing performance. You will be tasked with creating a reproducible environment and golden reference solution for the problem.

Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.

• Contribute expert-level code samples, debugging strategies, and development insights in Python3, Java, Rust, Go, C++, or TypeScript.
• Analyze, troubleshoot, and resolve complex software defects and performance bottlenecks in diverse codebases.
• Implement robust new features, ensuring scalability, maintainability, and adherence to software best practices.
• Refactor and optimize legacy code to improve clarity, efficiency, and long-term reliability.
• Document technical reasoning, solution approaches, and code decisions to enhance AI training data quality.
• Review and validate peer-contributed code and technical submissions for accuracy and clarity.

Work arrangement: Fully remote

• Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.