Research Staff, Voice AI Foundations

📋 Description Pioneer the development of Latent Space Models (LSMs) to solve data, scale, and cost challenges in Build next-generation neural audio codecs for extreme low bit-rate compression and high fidelity Develop steerable generative models that synthesize diverse human speech from codec latent Create embedding systems that factorize codec latent space into interpretable dimensions Leverage latent recombination to generate synthetic audio data and train multimodal Design model architectures, training schemes, and inference algorithms optimized for hardware and 🎯 Requirements Strong mathematical foundation in statistical learning theory Deep expertise in foundation model architectures and scaling training across modalities Proven ability to bridge theory and practice with efficient implementation Demonstrated ability to build data pipelines for massive datasets Track record of designing controlled experiments for architectural innovations Experience optimizing models for deployment with hardware constraints 🎁 Benefits Be part of a leading platform in the Voice AI economy Work with advanced AI tools and technologies Opportunity to pioneer entirely new approaches in audio AI research Collaborate with a fast-paced, innovative team