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Hebrew Quality Assurance Lead (QAL)

SME Careers

AI Language Experts Contractor Ongoing
Israel Up to $55/hr June 12, 2026

Job description

About the Role

This is a remote, hourly contractor role for a Hebrew Quality Assurance Lead (QAL) responsible for overseeing quality, consistency, and contributor performance across Hebrew AI training projects.

You will review AI-generated Hebrew content as well as trainer and QA work, evaluate outputs against project guidelines and rubrics, provide actionable feedback, maintain quality documentation, support onboarding, and ensure contributors consistently meet project standards.

Your work will directly impact the quality of Hebrew-language training data used by leading AI companies and foundation-model laboratories.

Key Responsibilities

Quality Monitoring

  • Review Hebrew-language submissions and conduct spot checks
  • Identify quality issues, recurring errors, and guideline violations
  • Provide clear and actionable feedback to contributors
  • Escalate critical or repeated quality concerns

Trainer & QA Communication

  • Communicate project updates and workflow changes
  • Share new guidelines and quality expectations
  • Ensure trainers and QAs remain aligned with project requirements

Question Handling

  • Respond to contributor questions promptly
  • Clarify instructions, translation requirements, linguistic edge cases, cultural nuances, and Hebrew language standards, gendered language usage, RTL formatting requirements, and localization terminology
  • Help contributors understand project expectations and quality standards

Contributor Activation Management

  • Follow up with inactive contributors
  • Encourage participation and activation
  • Track contributor engagement and availability
  • Escalate staffing or participation concerns when necessary

Documentation Management

  • Create and maintain Hebrew style guides, FAQs, trackers, quality notes, example libraries, honeypots, and onboarding materials
  • Ensure documentation remains accurate and current

Onboarding & Training

  • Conduct onboarding sessions for trainers and QAs
  • Explain workflows, rubrics, quality standards, and Hebrew language requirements
  • Support continuous learning and quality improvement

Quality Alignment

  • Ensure consistent application of Hebrew language guidelines
  • Monitor compliance with evolving requirements
  • Promote standardization across contributors and teams

Process Improvement

  • Identify recurring quality gaps and recommend workflow enhancements
  • Help develop scalable QA systems and best practices for Hebrew-language projects

Required Skills & Qualifications

  • Native or near-native Hebrew proficiency and strong professional English proficiency
  • 3+ years of professional experience in Hebrew writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows
  • Strong understanding of Hebrew grammar, spelling conventions, punctuation, tone, register, and cultural context, right-to-left (RTL) script handling, and gendered language conventions
  • Ability to identify mistranslations, literal phrasing, unnatural language, hallucinated claims, ambiguity, and terminology inconsistencies
  • Ability to evaluate work against detailed rubrics and guidelines
  • Strong written communication, feedback, and organizational skills

Preferred Qualifications

  • Experience leading or supporting trainers, annotators, editors, reviewers, or QA teams
  • Experience with AI training, data annotation, LLM evaluation, prompt/response evaluation, and rubric-based QA
  • Familiarity with Discord, Google Docs, Google Sheets, dashboards, and project management systems
  • Experience with Hebrew localization, UX writing, or RTL content projects

Additional Information

  • Fully remote work
  • Flexible schedule
  • Weekly payments
  • Access to future opportunities through the SME Careers expert network

About SME Careers

SME Careers is an AI data services company and subsidiary of SuperAnnotate that provides training data for many of the world's leading AI companies and foundation-model laboratories.

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