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Software Engineering AI Trainer; Sweden

Job in Los Angeles, Los Angeles County, California, 90001, USA
Listing for: Anyone AI Inc.
Part Time position
Listed on 2026-10-30
Job specializations:
  • Software Development
    Software Testing, Software Engineer, Backend Developer
Salary/Wage Range or Industry Benchmark: 96000 - 179000 USD Yearly USD 96000.00 179000.00 YEAR
Job Description & How to Apply Below
Position: Software Engineering AI Trainer (Sweden)

Anyone AI is recruiting skilled software engineers 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/Type Script; 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
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