At a Glance
- Tasks: Design and evaluate coding tasks, fix bugs, and implement features in a remote setting.
- Company: Join Anyone AI, collaborating with a leading AI lab on exciting projects.
- Benefits: Flexible hours, competitive pay per project, and the freedom to work remotely.
- Other info: Enjoy a part-time role with opportunities for growth and collaboration.
- Why this job: Make an impact in AI while honing your coding skills in a dynamic environment.
- Qualifications: 3-7 years of software engineering experience and strong Python skills required.
Anyone AI is recruiting skilled Python 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:
- 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
