Full-Stack Developer - AI Trainer
- Role
- Fullstack
- Experience
- Senior
- Employment
- Contract
Open to SE only. Set where you work from to check your eligibility.
No BS summary
Full-stack developer in Sweden with 3–7 years of professional software engineering experience. Needs strong Python and JavaScript/TypeScript, backend or full-stack production experience, testing frameworks, and advanced written English.
Core skills
Required skills
Required languages
Anyone AI is recruiting skilled Full-Stack Developers to work on a project with a leading AI lab.
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 evaluate realistic software engineering tasks, including bug resolution, feature implementation, refactoring/migration, and test generation.
- Create complex coding scenarios.
- Review peer submissions for quality and accuracy.
- 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.
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.
- Backend or full-stack development experience in production systems.
- Experience with testing frameworks such as pytest, Jest, JUnit, xUnit, or Go testing.
- Proven ability to debug and navigate large, multi-file codebases.
- Experience with code reviews, refactoring, and production migrations.
- Part-time, project-based expert evaluation work.
- Project-based consultant role.
- Consultants control their own schedule, provide their own tools, and may simultaneously provide services to other vendors/employers, subject to those vendors’ allowances.
Benefits
- Consultants control their own schedule.
- Consultants 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.