Backend Developer - AI Trainer
- Role
- Backend
- Experience
- Mid
- Employment
- Part-time
Open to FR, IN, NL only. Set where you work from to check your eligibility.
No BS summary
Backend developer / AI Trainer, 3–7 years of professional software engineering experience. Strong Python and JavaScript/TypeScript skills; working knowledge of Java, C# or Go. Must be located in France; part-time, project-based consultant (remote).
Core skills
Required skills
Optional languages
Anyone AI is recruiting skilled Backend Developers to work as a project consultants.
Qualifications:
- Advanced professional written proficiency in English
- 3–7 years of professional software engineering experience
- Strong proficiency in Python and JavaScript/TypeScript; working knowledge of Java, C#, or Go
- Backend or full‑stack development experience in production systems
- Experience with testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing)
- Proven ability to debug and navigate large, multi‑file codebases
- Experience with code reviews, refactoring, and production migrations
Engagement: Part-time, project-based expert evaluation work
Work Type: Remote
Contributors will design and evaluate realistic software engineering tasks, including bug resolution, feature implementation, refactoring/migration, and test generation. Work includes both creating complex coding scenarios and reviewing peer submissions for quality and accuracy.
This is a project-based consultant role. Consultants will be paid on a per-project basis; hourly rates are estimates based on anticipated completion time. Consultants control their own schedule, provide their own tools, and may simultaneously provide services to other vendors/employers (subject to those vendors’ allowances).
Responsibilities:
Contributors will:
- Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing
- Write clear natural-language specifications and reference implementations
- Develop and extend unit and integration test suites
- Review peer-generated tasks for correctness, clarity, and realism
- Identify edge cases, ambiguities, and potential failure modes
- Ensure alignment between specifications, code, and expected outputs
Expected Outcomes:
- High-quality, production-realistic coding tasks
- Complete and correct reference implementations
- Robust test coverage and validation artifacts
- Structured, actionable peer review feedback
What you'll do
- Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing
- Write clear natural-language specifications and reference implementations
- Develop and extend unit and integration test suites
- Review peer-generated tasks for correctness, clarity, and realism
- Identify edge cases, ambiguities, and potential failure modes; ensure alignment between specifications, code, and expected outputs
- Write clear natural-language specifications and complete reference implementations
- Develop and extend unit and integration test suites and validation artifacts
- Review peer-generated tasks for correctness, clarity, and realism; provide structured, actionable feedback
- Identify edge cases and ambiguities; ensure alignment between specifications, code, and expected outputs
- Identify edge cases, ambiguities and potential failure modes; ensure alignment between specifications, code, and expected outputs
What they require
- Advanced professional written proficiency in English
- 3–7 years of professional software engineering experience
- Strong proficiency in Python and JavaScript/TypeScript
- Working knowledge of Java, C#, or Go
- Experience with testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing)
- Strong proficiency in Python and JavaScript/TypeScript; working knowledge of Java, C#, or Go
- Backend or full‑stack production development experience; proven ability to debug and navigate large multi-file codebases
- Experience with testing frameworks, code reviews, refactoring, and production migrations
- Backend or full‑stack development experience in production systems
- Experience with testing frameworks (e.g., pytest, Jest, JUnit, xUnit, Go testing) and proven ability to debug large, multi-file codebases
Benefits
- Paid on a per-project basis (hourly estimates provided)
- Remote work
- Consultants control their own schedule and provide their own tools
- May simultaneously provide services to other vendors/employers (subject to those vendors’ allowances)
We create high-quality STEM training data for frontier AI models. Our data is used directly in training and evaluation pipelines at leading AI labs to improve model reasoning in technical domains.