Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
AI Trainers Network – Hebrew
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- Remote from
- 🌐 Anywhere
- Salary
- Undisclosed
- Department
- Data Science & Analytics
- Employment
- Full Time
- Experience
- Open level
- Published
- Apply before
- 3 Dec 2026
- Listing views
- 19
- Application actions
- 0
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About this role.
Welo Data, part of Welocalize, is a global AI data company with 500,000+ contributors delivering high-quality, ethical data to train the world’s most advanced AI systems. We’re building smarter, more human AI with a diverse community in 100+ countries.
At Welo Data, Limitless AI. Limitless You. isn’t just a slogan—it’s our promise. We build smarter AI through the power of human contribution, offering limitless opportunities for our global community to grow, contribute, and work on their terms.
Are you detail-oriented and curious about tech?
Welo Data is building a global network of linguists, language enthusiasts, and culturally aware contributors to shape safer, smarter AI.
By joining our talent community, you’ll be first in line for flexible, remote projects in annotation, evaluation, and prompt creation—always on your terms.
Note: This is not an active job opening. By applying, you’ll join our global contributor network. When a project aligns with your skills and availability, we’ll reach out with all the details, including scope, timeline, and compensation.
What You’ll Need
– Native or near-native fluency in Hebrew
– Based in: Israel, Canada, France, Austria, Spain
– English proficiency
– Comfortable with digital tools
– Detail-oriented and curious
Why Join Us?
🚀 Limitless You – Work when and where you want, with room to grow
🤖 Limitless AI – Contribute to smarter, more inclusive AI
🌎 Be Part of Us – Join a global, supportive community
About our projects:
Welo Data projects vary by scope and complexity, but all play a role in building more accurate, inclusive, and human-centered AI.
Depending on your skills, you might:
📝 Annotate or label text, images, or audio to train AI systems
🔍 Evaluate search results, ads, or chatbot responses for quality and relevance
💬 Create and test prompts to improve large language models (LLMs)
🌍 Ensure content reflects cultural, linguistic, or industry-specific accuracy
Some projects last a few days; others may extend over several weeks. Before each one, you’ll receive clear details on tasks, timelines, and compensation, so you can decide what works best for you.
How to Apply?
Click the “Apply” button on our website to fill out a short form and join our talent database. It only takes a few minutes to get started and become part of our growing community.
📬Questions?
If you have any questions about the process, feel free to contact us at TalentRequests@welocalize.com.
Compensation
Additional Information
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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The role, at a glance.
This is a talent-community opportunity for Hebrew-speaking AI trainers rather than an immediately active vacancy. Contributors may be matched with remote projects involving data annotation, search and chatbot evaluation, prompt creation, and cultural-linguistic quality review. The role requires native or near-native Hebrew, English proficiency, comfort with digital tools, and strong attention to detail. Projects vary in duration from a few days to several weeks, with scope, timelines, and pay shared before a contributor accepts an assignment. Eligible contributors must be based in Israel, Canada, France, Austria, or Spain.
Role DNA
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Pace & Pressure
3/5Autonomy Level
5/5Communication Load
3/5Salary analysis
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Core skills
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Sample interview questions
I would first study the project guidelines and examples, document edge cases, and apply the same decision criteria throughout the task. I would periodically review earlier work to confirm that my labels remain consistent and raise ambiguous cases through the designated quality process.
I would assess factual relevance, clarity, tone, grammar, and whether the wording is natural in Hebrew. I would also check for cultural context, unintended bias, unsafe content, and whether the response directly addresses the user’s request.
I would review all available documentation and examples before making assumptions. If the ambiguity could affect quality, I would record a concise example of the issue and ask the project contact for clarification rather than applying an inconsistent interpretation.
A strong test prompt has a clear objective, sufficient context, and criteria that make the output assessable. For Hebrew testing, I would also consider dialect, formality, cultural context, and scenarios that reveal whether the model understands nuanced language use.
I plan my availability realistically, review the expected scope and deadline before accepting work, and break tasks into measurable checkpoints. I communicate early if I encounter a blocker and complete quality checks before submitting deliverables.
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