Hebrew-Speaking Audio Evaluation Expert

You will listen to Hebrew audio clips and assess whether the speech or model output sounds fluent, natural, and linguistically authentic. You will compare audio with project guidelines and explain your decisions clearly.

Your feedback will help improve systems that understand and generate Hebrew. Reviews must be accurate, supported by clear reasons, and completed on time.

• Evaluate Hebrew audio for fluency, naturalness, pronunciation, and intonation.
• Review other linguistic characteristics against established guidelines.
• Write concise feedback and detailed justifications in English.
• Clarify ambiguous language content and document your findings.

What It Pays and Takes

This is an entry-level, part-time contractor role. Helpful background includes linguistics, phonetics, voice work, music, audio engineering, audio analysis, transcription, linguistic assessment, media, communications, or teaching.

• Pay: $30 to $65 per hour.
• Work type: Part-time contract work.
• Language: Professional proficiency in spoken and written Hebrew.
• English: At least B2 proficiency for written and verbal communication.
• Skills: Strong attention to detail and the ability to explain nuanced language differences clearly.
• Communication: Excellent written and verbal communication skills are required.
• Location: Open to candidates in the United Arab Emirates, Argentina, Austria, Bangladesh, Belgium, Bahrain, Brazil, Canada, Switzerland, Chile, Colombia, Germany, Denmark, Algeria, Egypt, Spain, France, the United Kingdom, Ghana, Greece, Indonesia, India, Italy, Jordan, Japan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan, Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, the Netherlands, Oman, Peru, the Philippines, Pakistan, Palestine, Portugal, Qatar, Saudi Arabia, Singapore, Thailand, Tunisia, Taiwan, the United States, Uzbekistan, Vietnam, and South Africa.

How It Works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI Training Work

AI training is the human work behind systems that understand language, audio, images, and text. Reviewers assess examples and give clear feedback so these systems improve, and people with strong language or specialist skills can contribute to this work remotely.