• Identify and correct audio artifacts, loudness inconsistencies, frequency imbalances, and sibilance issues across large-scale voice datasets. • Design and implement scalable audio processing pipelines for voice data • Define and implement scalable audio processing pipelines (EQ, compression, de-essing, dynamic range optimization) and normalization strategies across inter- and intra- voice recordings. • Optimize audio quality across real and synthetic voices to ensure a consistent product experience across multiple use cases. • Lead audio quality decisions during on-site voice actor recording sessions, including microphone selection, placement, gain staging, and environment setup. • Define, document, and enforce audio quality standards for external vendors, including recording setup requirements, signal characteristics, and post-processing expectations, ensuring vendor-produced audio meets Deepgram’s training and product needs even when recordings are not done on-site. • Convert expert-driven, manual audio workflows into automated, repeatable, code-based systems. • Collaborate closely with research to improve training data quality, especially TTS speaker-specific fine-tuning. • Contribute to synthetic data pipelines by defining and validating acoustic characteristics, guiding how different “sound profiles” should be produced and evaluated.