AI-Data Labeling Winternship

We’re building an in-house AI data labelling team this winter.Not freelancers.Not gig workers.A structured community working on production-grade AI and GenAI systems.Introducing the AI-Data Labeling Winternship at Akai Space.Most people only see AI as a finished product; a smaller group shapes how it learns and what “good” looks like.This winternship is for people who want to do that work seriously, not as filler.Who can apply?People from any background: arts, humanities, science, commerce, engineering, design, psychology, media, or self-taught.You don’t need to code. If you understand what AI is, are curious about how it is trained, and can follow clear guidelines carefully, you’re eligible.What this is* Paid, in-house AI data labelling work* Text, audio, image, and video datasets* Clear guidelines, quality calibration, and feedback loops* Long-term projects for high performers* Growth into QA and Lead roles over timeWhat we value* Attention to detail over speed* Consistency over guesswork* Learning and feedback over egoWe’re opening limited seats for this winter cohort and will review applications on a rolling basis.If this resonates, apply for the AI-Data Labeling Winternship here:If you know someone who fits this mindset, share this post.

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