Audio Engineer

The role

You will be the in-house audio expert setting audio standards and recording specs. You will help contributors fix recording setups and manage the QA team to deliver high-quality training data.

What you will do

• Be the audio authority for Ops, Engineering, and ML
• Define audio quality standards and recording specs
• Help contributors diagnose and fix home recording setups
• Write setup guides, onboarding checks, and troubleshooting docs
• Lead and calibrate a team to company audio standards
• Define acoustic targets for processed, synthetic, or AI-generated audio
• Work with ML researchers to define audio events and acoustic quality issues
• Turn definitions into actionable guidelines for audio QAs
• Manage the QA team in a rapid iteration loop
• Conduct quality audits on annotation and post-processing models

Required qualifications

• 7+ years in audio engineering, recording, or production (studio, broadcast, podcast, post, or voice work)
• A highly trained ear for subtle differences across voices, mics, rooms, and signal chains
• Deep hands-on knowledge of mics, interfaces, preamps, acoustics, and room treatment
• Strong DAW skills and fluency with loudness/metering, EQ, dynamics, noise reduction, and restoration tools (e.g., iZotope RX)
• Ability to troubleshoot remotely and explain fixes clearly to non-technical people
• Comfortable in a fast-moving startup: ambiguous problems, shifting priorities, high ownership

Nice to have

• Experience with speech or voice data for AI (TTS, ASR, SFT projects) at a lab or data vendor
• Experience recording voice actors or directing dialogue sessions
• Experience supporting remote or distributed recording at scale
• Scripting basics (Python, ffmpeg, SoX) for batch checks or processing
• Multilingual

Before you apply

• We sponsor international candidates across a range of visa types, including H-1B transfers, H-1B1, O-1, E-3, and TN, and we support STEM OPT

About the company

David AI builds and licenses high-quality voice and audio datasets to the world's leading AI labs. It is a ~50-person Series B team running data collection across ~20 language markets.