Quick facts
- Pay
- $1200–1600 per task
- Type
- Part-time
- Location
- New York, New York, United States
- Languages
- English, Polish, Finnish, Hebrew
- Platform
- Mindrift — 817 open jobs
- Typical pay at Mindrift
- $73–100/hour · median $73 (156 jobs on our site)
- Payout
- Bank transfer, PayPal, Tipalti, Payoneer (twice a month · min $5)
- Apply
- Free to apply — never pay to get AI training work
Mindrift is running a research study on how people use their phones, apps, and everyday digital tools, and how that differs across languages and cultures. We’re looking for bilingual participants in New York to join a paid, 3-day in-person study in Midtown Manhattan.
Why your language matters
Most technology is still designed with English speakers in mind. This study helps researchers understand how people who use other languages every day interact with their devices, so future products work better for them.
What you’ll do
- 1–3 days with our research team in Midtown Manhattan
- Walking the team through how you use your phone and favourite apps day to day
- Sharing examples of your everyday phone activity. You choose what to include
- A short questionnaire about your habits
Who we’re looking for
- 18+ and currently living in NYC
- Fluent in one of these languages: Finnish, Polish, Arabic or Hebrew
- You use this language in daily life (texting, email, notes)
- You’ve used a smartphone as your main personal phone for 3+ years
- Comfortable communicating in English
- Available for 3 consecutive days (Mon–Wed or Thu–Sat)
- Not currently working for a tech or AI company (to avoid conflicts of interest)
Compensation
$1,200–1,600 for the full study.
Simple and transparent
Participation is voluntary and covered by a signed consent form that explains exactly what’s involved. You can ask questions at any point and stop whenever you like.
How to apply
Register on Mindrift and complete a short screening questionnaire. We’ll confirm your session dates once you’re shortlisted.
Mindrift is the AI-tutor platform from Toloka. It recruits writers, editors and domain experts to create and review data used to fine-tune large language models.