Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems.
Remote Evaluation & Quality Jobs in Argentina 2026
183 remote jobs open to candidates in Argentina in Evaluation & Quality. Updated daily.
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems.
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems.
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems.
Your job is to serve as the human quality bar for AI-generated code. You will review solutions to programming tasks ranging from simple algorithm problems to multi-file application scaffolding.
We need evaluators who can read AI-generated text critically and make consistent quality judgments under detailed rubrics. On a given day you might compare two explanations of quantum mechanics, two pieces of marketing copy, and two responses to a sensitive personal question.
We need evaluators who can read AI-generated text critically and make consistent quality judgments under detailed rubrics. On a given day you might compare two explanations of quantum mechanics, two pieces of marketing copy, and two responses to a sensitive personal question.
Quality review sits between the annotation team and the client. You will sample completed batches, apply the scoring rubric, and produce accuracy reports that the project lead uses to give feedback to annotators.
We need people who can think like attackers. You will methodically test AI models against a taxonomy of failure modes: harmful content generation, jailbreak susceptibility, PII leakage, bias amplification, and more.
You will audit completed annotations produced by other team members, checking each one against the project rubric and flagging errors.
You will evaluate code generated by AI models. Each task shows you a programming prompt and one or more candidate solutions. Your job is to assess correctness, efficiency, readability, and adherence to best practices, then rank the solutions and write a brief justification.
We need evaluators who can read AI-generated text critically and make consistent quality judgments under detailed rubrics. On a given day you might compare two explanations of quantum mechanics, two pieces of marketing copy, and two responses to a sensitive personal question.
This role is adversarial by design. You will probe language models for weaknesses by writing creative, unusual, and sometimes uncomfortable prompts designed to surface failure modes.
We need people who can think like attackers. You will methodically test AI models against a taxonomy of failure modes: harmful content generation, jailbreak susceptibility, PII leakage, bias amplification, and more.
We need evaluators who can read AI-generated text critically and make consistent quality judgments under detailed rubrics. On a given day you might compare two explanations of quantum mechanics, two pieces of marketing copy, and two responses to a sensitive personal question.
You will evaluate code generated by AI models. Each task shows you a programming prompt and one or more candidate solutions. Your job is to assess correctness, efficiency, readability, and adherence to best practices, then rank the solutions and write a brief justification.
You will audit completed annotations produced by other team members, checking each one against the project rubric and flagging errors.
You will audit completed annotations produced by other team members, checking each one against the project rubric and flagging errors.
This role is about making judgment calls on AI output quality. You will see prompts across a wide range of topics -- math, coding, creative writing, factual questions, safety scenarios -- and rate the corresponding model responses on dimensions like helpfulness, truthfulness,…
Quality review sits between the annotation team and the client. You will sample completed batches, apply the scoring rubric, and produce accuracy reports that the project lead uses to give feedback to annotators.
You will sit at the intersection of AI training and human judgment. Each task presents a prompt-response pair (or set of pairs) that you evaluate against a detailed rubric covering accuracy, helpfulness, safety, and style.
We are seeking candidates to develop evaluation scenarios that test cutting-edge autonomous AI systems across multiple domains.
Rise Data Labs builds high-fidelity data services to power AI systems. We partner with leading research teams and industry stakeholders to improve model quality through human oversight, evaluation, and annotation.
Directly responsible for improving the quality, safety, and intelligence of cutting-edge AI models. Key Responsibilities Create High-Quality Training Data: Write, edit, and refine clear, accurate, and engaging prompts and responses on a diverse range of topics.