The Work
You will create realistic backend coding tasks for AI systems. These tasks will cover feature implementation and software bug fixes, with scenarios that test practical engineering judgment.
You will also build deterministic verifiers. These checks should accept reasonable, valid solutions and reject invalid ones while giving you a reliable way to assess model-generated code.
- Create backend tasks involving new features and bug fixes.
- Design challenging scenarios that reflect practical software engineering work.
- Build verifiers that distinguish valid solutions from invalid ones.
- Review solution quality and correctness using sound code review judgment.
- Use debugging, performance analysis, automated testing, and refactoring skills.
- Work with services, APIs, codebases, algorithms, and data structures as each task requires.
What It Pays and Takes
This is an individual contractor role with a flexible schedule of approximately 15 hours per week. Compensation is $30 to $100 per hour equivalent, paid per task that meets the project specifications.
- Pay: $30 to $100 per hour equivalent, paid per task that meets the project specifications.
- Hours: Approximately 15 hours per week, with a flexible schedule.
- Work arrangement: Individual contractor and part-time.
- Location: Open to candidates in the United Arab Emirates, Argentina, Austria, Bangladesh, Belgium, Bahrain, Brazil, Canada, Switzerland, Chile, Colombia, Germany, Denmark, Algeria, Egypt, Spain, France, the United Kingdom, Ghana, Greece, Indonesia, India, Italy, Jordan, Japan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan, Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, the Netherlands, Oman, Peru, the Philippines, Pakistan, Palestine, Portugal, Qatar, Saudi Arabia, Singapore, Thailand, Tunisia, Taiwan, the United States, Uzbekistan, Vietnam, and South Africa.
- Language: Professional fluency in English.
- Backend development experience with Java, Node.js, Go, Rust, TypeScript, Python, C++, or a similar language.
- Experience building scalable services and APIs.
- Ability to diagnose bugs and system bottlenecks.
- Experience implementing complex features and refactoring large applications.
- Strong knowledge of algorithms, data structures, and foundational computer science.
- Comfort with automated testing, code review, analytical problem-solving, and technical communication.
Helpful Background
Experience writing unit tests, designing test strategies, diagnosing flaky tests, or maintaining continuous integration test pipelines can help you build reliable coding tasks and verifiers. Prior AI training experience is not required.
- Unit test development
- Test strategy design
- Flaky test diagnosis
- Continuous integration test pipeline maintenance
How it works
You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.
About AI Training Work
AI training work is the human side of building AI systems. People create and review examples, including coding tasks and model responses, so systems can learn what useful and correct output looks like.