About this role
Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Skills
Audio Quality AssuranceAudio Artifact DetectionAudio RestorationAudio CleanupAudio EditingIndustry-standard Audio ToolsData AnnotationQuality ControlCritical ListeningStudio MonitorsHigh-end HeadphonesEnglish CommunicationIssue ReportingTeam CollaborationIndependent Remote WorkAttention To DetailTask PrioritizationTime ManagementAi/ml Data LabelingDistributed Team Collaboration
Key responsibilities
- Conduct detailed quality assurance on audio recordings, identifying and documenting artifacts or anomalies.
- Assess the severity of audio issues and classify them accurately for AI model training use.
- Perform audio cleanup and restoration tasks, ensuring data meets professional standards.
- Annotate audio and video data with clear, concise notes to support AI/ML development.
- Participate in labeling, review, and quality control processes for large-scale datasets.
- Leverage your expertise in audio engineering to identify best practices and share insights with the team.
- Collaborate effectively with a distributed team, providing regular feedback and contributing to a culture of high standards.
Required skills & qualifications
- Professional monitoring setup, including studio monitors or high-end headphones, suitable for critical listening tasks.
- Strong command of written and verbal English communication for precise issue reporting and team collaboration.
- Deep understanding of audio quality assurance processes and artifact detection methodologies.
- Experience with audio restoration, cleanup, and editing workflows using industry-standard tools.
- Ability to provide thorough, objective, and actionable feedback for audio data improvement.
- Familiarity with data annotation and quality control for AI or media workflows.
- Self-motivated, detail-oriented, and comfortable working independently in a remote environment.
Preferred qualifications
- Background in audio or video data labeling for machine learning or AI development.
- Experience collaborating in distributed audio engineering teams.
- Demonstrated ability to prioritize tasks and manage time effectively in a fast-paced setting.
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