Remote AI Code QA Coder (LatAm)

Outlier

La Serena

Remote

CLP 38,488,000 - 54,816,000

Full time

10 hours ago
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Benefits offered by this job

Remote work
Flexible schedule
Free access to leading LLMs

Job summary

Outlier is building a structured remote program where your software engineering skills help train AI models to generate, debug, and evaluate code. Open to all of Latin America.

As a QA Coder, you will review AI-generated code, rate and rank model responses across key dimensions, and craft clear computer science prompts to challenge AI systems. This is a 1099 contract opportunity with pay up to $34 USD/hr and potential incentive earnings.

Qualifications

  • Completed a Bachelor's degree in Computer Science from a selective institution.
  • Software engineering experience contributing to a live production codebase, ideally for a technology company.
  • Ability to articulate complex concepts fluently in written and spoken English.
  • Excellent attention to detail, including grammar, punctuation, and style guidelines.

Responsibilities

  • Review AI-generated code: read through code produced by AI models and flag errors, inconsistencies, or quality issues using structured guidelines.
  • Rate and rank model responses: score responses across key dimensions — accuracy, instruction following, and presentation — to help improve model output.
  • Write computer science questions: develop clear, well-structured prompts that challenge AI models and push the boundaries of their coding ability.

Skills

English proficiency
Attention to detail

Education

Bachelor's degree in Computer Science

Job description

Outlier is building a structured remote program where your software engineering skills help train AI models to generate, debug, and evaluate code. Open to all of Latin America.

As a QA Coder, you will review AI-generated code, rate and rank model responses across key dimensions, and craft clear computer science prompts to challenge AI systems. This is a 1099 contract opportunity with pay up to $34 USD/hr and potential incentive earnings.

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