Audio Quality AI Trainer at micro1

Job Title:Audio Quality AI Trainer

Job Type:Part-time, contract (min. ~15 to 20 hours a week)

Location:Remote

Job Summary

Join our customer's team as an Audio Quality AI Trainer and play an essential role in advancing the next generation of AI. You’ll evaluate short audio clips, expertly identify and classify audio artifacts, and deliver precise annotations that directly impact model accuracy. This is an exciting opportunity for someone passionate about audio quality, meticulous in their work, and eager to contribute to state-of-the-art AI development.

Key Responsibilities

• Analyze and classify audio artifacts such as noise, clipping, echoes, and compression issues in provided clips.
• Filter and repair audio artifacts using spectral/manual edits and standard restoration workflows to create clean, model-ready clips.
• Deliver detailed and accurate annotations to train and enhance AI audio models.
• Review and quality-assure annotations created by other team members to ensure consistency and correctness.
• Develop clear and comprehensive annotation notes, particularly for edge or ambiguous cases.
• Collaborate with the training team to refine project guidelines and boost agreement among annotators.
• Maintain a sharp attention to detail throughout classification and QA processes.
• Provide constructive feedback to continuously improve annotation quality and model performance.

Required Skills and Qualifications

• Professional experience in audio annotation, descriptive captioning, transcription, podcast/audio editing, or audio QA.
• Hands-on audio restoration experience: routine use of spectral repair, de-click/de-clip, denoise, de-reverb, EQ and manual fixes on short clips.
• Solid understanding of audio terminology and common recording faults.
• Proficiency with browser-based annotation tools and familiarity with common audio tools (e.g., iZotope RX, Adobe Audition, REAPER, or equivalent).
• Demonstrated ability to deliver before/after examples or quick demo edits
• Exceptional attention to auditory detail and the ability to recognize subtle audio discrepancies.
• Strong written and verbal communication skills, with a focus on clarity and precision.
• Demonstrated commitment to annotation accuracy and quality assurance best practices.
• Available to commit at least ~15–20 hrs/week for this project.

Preferred Qualifications

• Background in audio engineering, audio design, and audio restoration.