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2 дня назад

Teaching Assistant: Data Annotation (Somali Speaking)

Формат работы
remote (Global)
Тип работы
parttime
Грейд
middle
Английский
b2
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Teaching Assistant: Data Annotation (Somali Speaking) (AI Data Annotation): Supporting Somali learners in a fully virtual training-to-jobs program through live-session facilitation, annotation practice, exercise grading, and individual guidance with an accent on multimodal labeling, AI output evaluation, and data quality. Focus on explaining annotation guidelines, correcting labeling errors, reviewing portfolio projects, and helping learners build accuracy and consistency for remote work.

Location: Remote and open to candidates anywhere, provided they can reliably support learners during East Africa Time (EAT) program hours.

Company

hirify.global provides AI and data workforce development programs for enterprises, governments, and employers worldwide.

What you will do

  • Support a small group of learners throughout a fully virtual Data Annotation training-to-jobs program.
  • Monitor Pumble or Slack, answer learner questions, facilitate breakout rooms, and support hands-on labeling practice during live sessions.
  • Hold weekly office hours, review upcoming materials, and record short video walkthroughs for asynchronous assignments.
  • Review and grade labeling exercises and portfolio projects within seven days, giving feedback on accuracy and consistency.
  • Contact learners who miss sessions or fall behind, flag concerns, submit weekly progress reports, and attend weekly staff meetings.
  • Cover live lectures when assigned and help maintain session continuity if the Lead Instructor is unavailable.

Requirements

  • Professional working proficiency in both Somali and English, spoken and written, with the ability to explain technical content in both languages.
  • 3+ years of professional experience in data annotation, data labeling, AI training data, data quality, or a related role.
  • Experience with multimodal data labeling across text, speech and audio, image, and video.
  • Ability to interpret and apply detailed annotation guidelines; evaluate dialogue and AI outputs; rate and compare responses; and write clear human feedback.
  • Experience checking accuracy and consistency, identifying and correcting labeling errors, and handling confidential and secure data.
  • Understanding of AI fundamentals, including how labeled data is used to train AI systems.
  • Hands-on experience with annotation and labeling platforms.
  • Strong leadership, communication, collaboration, organizational, and attention-to-detail skills, plus empathy, flexibility, patience, and enthusiasm for supporting learners new to technology.
  • Experience working in a fully virtual environment and comfort with Zoom, Pumble or Slack, and online learning platforms.

Nice to have

  • Teaching, tutoring, or mentoring experience with adult learners.
  • AWS Certified AI Practitioner (AIF-C01) or an equivalent AI certification.
  • Arabic proficiency and familiarity with Maay and standard Somali.
  • Familiarity with the Somali context, including education access, connectivity, and remote work among young people in Somalia.

Culture & Benefits

  • Part-time contract program opportunity within the Expert Network.
  • Fully virtual program supporting young people in Somalia and preparing them for remote work with employers worldwide.
  • Live sessions are scheduled during EAT hours; program dates, session days, times, and cohort size will be shared with shortlisted candidates before commitment.
  • Mandatory pre-program TA onboarding includes program orientation, platform setup, and training materials.
  • Weekly office hours, learner support, staff meetings, and response expectations are part of the role.

Hiring process

  • Provide general availability for live sessions during EAT hours when applying.
  • Shortlisted candidates will receive the finalized program dates, live session schedule, and cohort size before making a commitment.

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