Bilingual Expert (Russian), Part-Time Audio Evaluation - Remote (51 Countries)
OpenTrain AI- $30-$65 per hour
- 100% remote
- Part-time contract
- Fully remote and flexible, no fixed shifts, no commute
Review Russian audio and explain your ratings in English to help improve speech AI.
AI training is the human work behind modern artificial intelligence. Teams need careful language reviewers to judge whether generated speech sounds clear, natural and accurate, then explain the reasons in plain English.
## What you will do
- Listen to Russian audio clips and rate fluency, pronunciation, intonation and naturalness.
- Follow evaluation guidelines consistently across assigned reviews.
- Write concise English feedback that explains each rating.
- Clarify ambiguous language content and complete reviews accurately and on time.
## Why this is worth your time
- Get paid $30-$65 an hour for careful speech-AI evaluation work.
- Work on speech AI systems that learn from careful language judgments.
- Apply Russian language expertise to audio quality and model feedback.
- Fully remote and flexible, with no fixed shifts and no commute.
## Who this is for
- Professional proficiency in spoken and written Russian.
- At least B2 proficiency in English for written and verbal communication.
- Strong attention to detail and clear written and verbal communication.
- Helpful background in linguistics, phonetics, voice work, music, audio engineering, audio analysis, transcription, language assessment, media, communications or teaching.
- No AI experience needed.
## Pay and details
- $30-$65 per hour as an independent contractor.
- Part-time, flexible schedule; fully remote in the listed countries.
## How to apply
1. Apply on OpenTrain with your resume: https://app.opentrain.ai/api/out/cmssqk9j3004l04ihhyhfxbaz?ch=remotenetwork&sub=remotenetwork-cmssqk9j3-ww-2026-10
2. Complete the application on the hiring site.
3. If shortlisted, take a short AI interview.
About OpenTrain AI: OpenTrain AI connects people with paid, part-time AI training and data-labeling work. Contributors review and improve examples that help AI systems understand and produce useful content.