The work
You will create reproducible coding tasks for AI systems. These tasks cover feature development, bug fixing, refactoring, and performance improvement across different codebases.
You will also build reference solutions and deterministic verifiers. Verifiers must accept reasonable correct solutions and reject incorrect ones. The role combines backend engineering, technical writing, code review, and the preparation of AI training data.
- Create coding tasks that test feature implementation, debugging, refactoring, and performance work.
- Build verifiers that assess whether proposed solutions are valid.
- Write code samples, debugging strategies, development insights, and technical reasoning.
- Analyze complex software defects and performance bottlenecks across large codebases.
- Refactor legacy systems to improve clarity, efficiency, scalability, and reliability.
- Review contributed code and technical submissions for accuracy and clarity.
What it pays and takes
This is a remote, part-time contractor opportunity for candidates in supported locations. The role is listed as entry level, but it requires strong hands-on software engineering skills and sound technical judgment.
- Pay: $50 to $100 per hour equivalent, paid per task that meets the project specifications.
- Typical task runs: approximately 15 hours.
- Expected commitment: at least 10 to 15 hours per week and less than 20 hours per week.
- Location: Open to candidates in Algeria, Argentina, Austria, Bahrain, Bangladesh, Belgium, Brazil, Canada, Chile, Colombia, Denmark, Egypt, France, Germany, Ghana, Greece, India, Indonesia, Italy, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Lebanon, Malaysia, Mexico, Morocco, the Netherlands, Nigeria, Oman, Pakistan, Palestinian Territories, Peru, the Philippines, Portugal, Qatar, Saudi Arabia, Singapore, South Africa, Spain, Sri Lanka, Switzerland, Taiwan, Thailand, Tunisia, the United Arab Emirates, the United Kingdom, the United States, Uzbekistan, and Vietnam.
- Language: Professional fluency in English.
- Strong hands-on expertise in Python, Java, Rust, Go, C++, TypeScript, or a similar programming language.
- Backend development experience building scalable services and APIs.
- Strong understanding of algorithms, data structures, software engineering principles, automated testing, and code review.
- Ability to debug complex systems, resolve bugs, optimize performance, and work with large codebases.
- Clear technical documentation and communication skills.
- Open source contributions and a public GitHub profile are valuable ways to show your engineering work.
- Experience delivering complex features, modernizing legacy systems, and explaining technical decisions is especially relevant.
- Previous AI experience is not required.
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 is the human work behind systems that learn from examples, including coding tasks, solutions, and reviews. Experienced contributors are paid for applying practical judgment to make those examples accurate and useful for improving AI systems.