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Remote
30 Open Positions
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500 Employees or more · Scientific Research & Development

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Job description

Job Title: Audio Engineer


Job Type: Contractor


Location: Remote (US and Canada)


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.


Key Responsibilities:

  1. Conduct detailed quality assurance on audio recordings, identifying and documenting artifacts or anomalies.
  2. Assess the severity of audio issues and classify them accurately for AI model training use.
  3. Perform audio cleanup and restoration tasks, ensuring data meets professional standards.
  4. Annotate audio and video data with clear, concise notes to support AI/ML development.
  5. Participate in labeling, review, and quality control processes for large-scale datasets.
  6. Leverage your expertise in audio engineering to identify best practices and share insights with the team.
  7. Collaborate effectively with a distributed team, providing regular feedback and contributing to a culture of high standards.


Required Skills and Qualifications:

  1. Professional monitoring setup, including studio monitors or high-end headphones, suitable for critical listening tasks.
  2. Strong command of written and verbal English communication for precise issue reporting and team collaboration.
  3. Deep understanding of audio quality assurance processes and artifact detection methodologies.
  4. Experience with audio restoration, cleanup, and editing workflows using industry-standard tools.
  5. Ability to provide thorough, objective, and actionable feedback for audio data improvement.
  6. Familiarity with data annotation and quality control for AI or media workflows.
  7. Self-motivated, detail-oriented, and comfortable working independently in a remote environment.


Preferred Qualifications:

  1. Background in audio or video data labeling for machine learning or AI development.
  2. Experience collaborating in distributed audio engineering teams.
  3. Demonstrated ability to prioritize tasks and manage time effectively in a fast-paced setting.
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