Audio Engineer - Pro Tools

Audio Engineers – Pro Tools (Contract)
Remote (UnitedStates preferred)

Shape the data that powers frontier AI.

Quick facts

Engagement – Hourly, at‑will contractor

Schedule – Fully remote & asynchronous (min. 15 hrs/week)

Pay Range (US) – $25–$50 per hour

Start Date – Rolling — staffed as projects launch

What you’ll do

Produce, mix, and master high‑quality audio content according to project specifications and industry standards.

Work efficiently in Pro Tools to edit, balance, and enhance multi‑track recordings.

Review and refine audio for clarity, consistency, and technical accuracy.

Evaluate AI‑assisted audio outputs for quality, alignment, and production integrity.

Provide constructive feedback to improve AI‑driven audio processing and production tools.

You’re a great fit if

Experience in audio engineering, sound design, or music production with a strong command of Pro Tools (Required).

Access to professional‑grade audio equipment and a quiet, acoustically treated workspace (Required).

Proven ability to deliver high‑quality mixes and masters efficiently and consistently.

Exceptional attention to detail in audio balance, clarity, and technical precision.

Interest in AI‑driven audio processing, sound analysis, or machine learning applications in music and sound.

Bonus: Experience with audio dataset creation, labeling, or AI audio model training projects.

About the role

Flexible workload – work from anywhere, on your own schedule.

High impact – your craft directly improves models used by top AI labs & Fortune 500 teams.

Clear ownership – know exactly what success looks like and have autonomy to deliver.

Growth potential – consistent high performers spearhead new programs and mentor incoming SMEs.

Interview process

Complete a screening with Zara, our AI interviewer in English, to learn more about your background and experience.

About Labelbox
Labelbox builds the data engine that accelerates breakthrough AI. Our platform, expert services, and marketplace let teams iterate on data as nimbly as they iterate on code, enabling safer, smarter models in production. We’re backed by SoftBank, Andreessen Horowitz, BCapital, GradientVentures, DatabricksVentures, and Kleiner Perkins, and trusted by leading research labs and enterprises worldwide.

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