Multilingual Reviewers/QA – 7 Languages, 100 Resources

@Toishi334

I am a native Japanese linguist with extensive experience annotation and QA experience with similar projects (audio and text content). I have reviewed, revised, or added comments for annotation projects relating to various AI training projects. I would be grateful to participate in your project while adhering to your guidelines. Please refer to my details below: 1. Which language(s) you/your team can support - Japanese 2. Number of reviewers you can provide per language - 1 3. Your proposed hourly rate per language - USD 18 4. Native or near-native fluency + prior QA/annotation review experience - Native Japanese with similar experience 5. Earliest start date - Today Please contact me with instructions, which I will review prior to starting the project. I look forward to hearing from you. Toru

@sangikpark0716

Hello, We can support the Bengali dataset immediately. • 1 native Bengali reviewer is ready now; we can expand to 5 reviewers after the calibration batch is approved. • The work will be managed by a Korean project manager with prior experience supporting data-labeling workflows. • We will review accuracy, consistency, and completeness against your guideline and maintain a clear discrepancy/issue log. • Proposed Bengali rate: INR 200/hour. • Earliest start: immediately. To make the first engagement low-risk, we can complete a 20-item calibration sample at no charge. We will scale only after you approve the review quality. We can also provide daily reviewed-item counts and QA summaries. Please share the guideline and a small non-sensitive sample when ready.

@pratyushac01

I’m interested in supporting the Telugu dataset review. • Language: Telugu • Reviewers: 3 • Fluency: Native Telugu • QA experience: 4 years • Rate: ₹200/hour • Availability: Immediate I’m a QA Engineer with 4 years of experience in systematic quality validation across web, mobile and backend applications. My professional work requires careful checking of accuracy, consistency, completeness and deviations against defined requirements, which aligns closely with this review task. For the Telugu dataset, I will review each annotated item against your guidelines, identify incorrect or inconsistent annotations, flag missing information and maintain consistent standards throughout the assigned volume. I’m comfortable with detailed, repetitive review work while maintaining strong attention to small differences and ensuring every item is checked carefully. I can also maintain a clear discrepancy log so corrections can be tracked efficiently. My primary background is software QA rather than data annotation, so I will not overstate my experience. However, QA has trained me to follow precise criteria, identify subtle inconsistencies and document findings clearly and objectively. I’m available to start immediately and can handle the required review workload. I’d be happy to complete a calibration sample so you can evaluate the quality of my Telugu review before assigning the full dataset.