Remote AI Code QA Engineer

Outlier; Buenos Aires; Remote; ARS 59.420.000 - 72.153.000; Vollzeit

Benefits dieser Stelle

Up to USD 34/hr pay

Additional mission incentives

Free access to leading LLMs

Zusammenfassung

Outlier offers a structured remote program designed for LatAm's top software engineers to help train AI models in code generation, debugging, and evaluation. The role is open to applicants across Latin America, with compensation up to $34 USD/hr plus incentives.

As a QA Coder, you will review AI-produced code, rate model responses, and craft clear computer science prompts to challenge the models while contributing to state-of-the-art AI research.

Qualifikationen

• 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.

Aufgaben

• 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.

Kenntnisse

Production codebase experience

English fluency

Attention to detail

QA testing

Ausbildung

Bachelor's degree in Computer Science

Jobbeschreibung

Outlier offers a structured remote program designed for LatAm's top software engineers to help train AI models in code generation, debugging, and evaluation. The role is open to applicants across Latin America, with compensation up to $34 USD/hr plus incentives.

As a QA Coder, you will review AI-produced code, rate model responses, and craft clear computer science prompts to challenge the models while contributing to state-of-the-art AI research.