Research Staff, Voice AI Foundations - Remote

📋 Description

• Build next-generation neural audio codecs achieving extreme, low bit-rate compression and high
• Pioneer steerable generative models that can synthesize the full diversity of human speech from the
• Develop embedding systems that factorize the codec latent space into interpretable dimensions such
• Leverage latent recombination to generate synthetic audio data at scale and train multimodal
• Design model architectures, training schemes, and inference algorithms optimized for hardware to

🎯 Requirements

• Strong mathematical foundation in statistical learning theory, particularly in self-supervised and
• Deep expertise in foundation model architectures and scaling training across modalities
• Proven ability to bridge theory and practice in deriving and implementing novel mathematical
• Demonstrated ability to build data pipelines for massive datasets with quality and diversity
• Track record of designing controlled experiments to isolate architectural impacts
• Experience optimizing models for real-world deployment, including hardware constraints and