Full remote
2 giorni fa
Italia
Anyone AI Inc.
Tempo pieno
Gratuito con email o Google
Salva questo lavoro e mantieni la tua ricerca organizzata
Crea un account gratuito per salvare lavori, creare avvisi e tornare a questa inserzione dalla tua dashboard.
Gratuito con email o Google
Continuando accetti i nostri Termini & Informativa sulla privacy.
Anyone AI is recruiting skilled software engineers who also speak Italian, 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
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