Overview

Portuguese QA Lead – Remote Jobs in Timor-Leste at YO IT Consulting

Title: Portuguese QA Lead – Remote

Company: YO IT Consulting

Location: Timor-Leste

Job Description

Job Title: Portuguese Quality Assurance Lead

Job Type: Contract

Location: Remote

About This Role

In this hourly, remote contractor role, you will work as a Portuguese Quality Assurance Lead to oversee quality, consistency, and trainer performance across Portuguese AI training projects. You will review AI-generated Portuguese content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for accuracy, fluency, grammar, spelling, tone, cultural appropriateness, meaning preservation, instruction-following, formatting, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Portuguese quality leadership will directly help improve the world’s premier AI models by ensuring that Portuguese training data is natural, accurate, culturally appropriate, well-documented, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

Your Profile

  • Bachelor’s or Master’s degree in Portuguese, Linguistics, Translation, Communications, Journalism, English, Education, Quality Assurance, or a relevant domain/related field.
  • Native or near-native Portuguese proficiency with strong reading and writing skills.
  • Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear feedback in English.
  • 3+ years of professional experience in Portuguese writing, editing, translation, localization, content QA, AI training, education, annotation, or related workflows.
  • Strong understanding of Portuguese grammar, spelling, punctuation, tone, register, regional usage, cultural context, and Brazil-specific localization.
  • Ability to evaluate Portuguese content against rubrics and identify issues such as mistranslation, literal phrasing, European Portuguese mismatch, unnatural tone, hallucinated claims, ambiguity, or inconsistent terminology.
  • Experience leading or supporting remote teams of trainers, annotators, reviewers, editors, or QAs is strongly preferred.
  • Comfortable with Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
  • Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, and documentation.
  • Experience with AI training, data annotation, LLM evaluation, prompt/response evaluation, or rubric-based LLM QA is a strong plus.

Key Responsibilities

  • Spot-check Portuguese items, identify issues, provide feedback through DMs, and escalate recurring or critical issues.
  • Update trainers/QAs on Discord about guidelines, project changes, workflow updates, and quality expectations.
  • Respond to questions around Portuguese grammar, tone, regional usage, translation fidelity, terminology, and cultural context.
  • DM inactive contributors, encourage activation, track follow-ups, and flag availability issues.
  • Create and maintain Portuguese documentation, style guides, trackers, FAQs, examples, honeypots, and onboarding materials.
  • Run onboarding/training calls for Portuguese contributors.
  • Ensure Portuguese guidelines are applied consistently.
  • Identify recurring quality gaps and improve QA workflows.
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