AI Audio Quality Assurance Engineer
About the Role
A high-impact AI initiative is seeking audio engineering professionals to support the development of next-generation machine learning systems through high-quality audio analysis and quality assurance workflows. The role focuses on improving training data reliability through precise evaluation, restoration, and annotation practices.
This opportunity is ideal for individuals with strong critical listening abilities, experience in professional audio environments, and the ability to maintain consistent quality standards in distributed remote teams. Candidates who are highly detail-oriented and comfortable working independently will align well with the demands of the role.
The work involves identifying audio artifacts, conducting restoration and cleanup tasks, annotating multimedia datasets, and supporting AI/ML quality control operations where accuracy, consistency, and structured reporting are critical.
What You'll Do
- Conduct quality assurance reviews on audio recordings to identify artifacts, distortions, and anomalies
- Classify and document audio issues for AI training and evaluation workflows
- Perform audio cleanup, restoration, and editing using professional audio software
- Annotate audio and video datasets with accurate and structured notes
- Support large-scale labeling and quality control operations for AI/ML datasets
- Evaluate audio consistency and maintain professional technical standards across deliverables
- Provide objective feedback to improve dataset quality and workflow efficiency
- Collaborate with distributed teams to maintain alignment on review standards and operational processes
- Track issues and communicate findings clearly through written reports and internal documentation
Requirements
- Professional audio monitoring setup including studio monitors or high-end headphones
- Strong understanding of audio quality assurance and artifact detection techniques
- Experience with audio restoration, editing, and cleanup workflows
- Proficiency with industry-standard audio engineering tools and software
- Strong written and verbal English communication skills
- Ability to deliver structured and actionable issue reports
- Experience with data annotation or media quality control workflows
- High attention to detail and strong critical listening skills
- Ability to work independently in a remote environment
- Strong task prioritization and time management capabilities
- Comfort collaborating within distributed teams and asynchronous workflows
- Preferred experience with AI/ML data labeling or training dataset operations
- Preferred background in remote audio engineering or large-scale review environments