Remote QA Coder for AI Code Training

Outlier

Panama City (FL)

Remote

USD 39,000 - 55,000

Full time

14 hours ago
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Benefits offered by this job

Remote work
1099 contract

Job summary

Outlier invites you to join a remote QA coder program designed to train AI models through real coding tasks. You review AI-generated code, rank model responses, and craft clear computer science prompts.

This is a freelance, 1099 opportunity with flexible scheduling and international eligibility. Participants work on discrete debugging and quality tasks, with compensation up to $34 USD/hr and additional incentive opportunities based on project performance.

Qualifications

  • Completed a Bachelor's degree or higher 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 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 to help improve model output.
  • Write computer science questions: develop clear, well-structured prompts that challenge AI models and push coding abilities.

Skills

English proficiency
Attention to detail
Production code experience
Software engineering basics

Education

Bachelor’s degree in Computer Science

Job description

Outlier invites you to join a remote QA coder program designed to train AI models through real coding tasks. You review AI-generated code, rank model responses, and craft clear computer science prompts.

This is a freelance, 1099 opportunity with flexible scheduling and international eligibility. Participants work on discrete debugging and quality tasks, with compensation up to $34 USD/hr and additional incentive opportunities based on project performance.

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