AI Work Central

Social Media Expert

SME CareersLanguagesFirst seen 9 Oct 2026

up to$55/hr as listed by SME Careers, USDEstimate a week at this rate
Apply on SME Careers

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Where
17 countries

United States, Germany, Brazil, India, Bangladesh, Bhutan, Indonesia, Cambodia, Sri Lanka, Malaysia, Nepal, Philippines, Pakistan, Singapore, Thailand, Timor Leste, Vietnam

Language
English
Type
Contract, remote

Posted on SME Careers First seen 9 Oct 2026Checked 12 Oct 2026

From the SME Careers listing

In this hourly, remote contractor role, you will work as a Social Media Subject Matter Expert (SME) to review AI-generated social content and social strategy outputs and/or create expert social media content, evaluating reasoning quality, audience fit, and step-by-step creative decision-making while providing precise written feedback. You will assess solutions for clarity, brand voice, platform fit, and adherence to the prompt; identify issues in messaging, hooks, structure, CTA effectiveness, compliance/claim risk, and community-safety considerations; fact-check claims where needed; write high-quality explanations and model posts that demonstrate strong social-first writing; and rate and compare multiple responses based on effectiveness, correctness, and reasoning quality. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your social media expertise directly helps improve the world’s premier AI models by making their social content more on-brand, engaging, accurate, and clearly explained.

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.

Responsibilities

  • Develop AI Training Content: Create detailed prompts and gold-standard social outputs (posts, threads, scripts, calendars, strategy notes) to guide AI learning.
  • Optimize AI Performance: Evaluate and rank AI responses to improve engagement, clarity, platform fit, and brand alignment.
  • Ensure Model Integrity: Test AI outputs for inaccuracies, unsafe/misleading claims, policy risks, and bias; validate reliability across use cases.

Requirements

  • Bachelor’s degree (or higher) in Marketing, Communications, Journalism, or a related field (or equivalent professional experience).
  • 5+ years of professional experience managing social media for brands (in-house or agency), including content creation and performance reporting.
  • Strong understanding of platform mechanics and best practices across Instagram, TikTok, X (Twitter), LinkedIn, YouTube Shorts, and Facebook (as relevant).
  • Proven ability to craft platform-native content: hooks, pacing, captions, CTAs, and concise storytelling tailored to audience intent.
  • Experience with content operations: content calendars, creative briefs, approvals workflows, and collaborating with design/video teams.
  • Comfort evaluating content for risk: misleading claims, policy violations, brand safety, and sensitive-topic handling.
  • Strong analytics instincts: reading performance signals (reach, watch time, CTR, saves/shares, CAC/ROAS basics) and turning data into iteration plans.
  • Minimum C1 English proficiency with excellent written communication and editing skills.
  • Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones.
  • Previous experience with AI data training/annotation, editorial QA, or content review workflows is strongly preferred.

Text above is the platform's own listing, shown as published. Check the details on SME Careers before applying.

Prepare for the assessment

Practice questions and what each platform says about its screening for this kind of role:

Terms in this listing

  • Prompt: The input given to a model: a question, an instruction or a conversation so far.
  • Annotation: Adding labels or notes to data such as text, images, audio or video so a model can learn from it.

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