Research Staff, Voice AI Foundations [Remote]
Core
Pioneering Latent Space Models (LSMs) to solve fundamental data, scale, and cost challenges in building robust, contextualized voice AI.
Role type
Research Staff, Voice AI Foundations
Builds
Next-generation neural audio codecs, steerable generative models, embedding systems, synthetic audio data, and multimodal speech-to-speech systems.
Domain
Voice AI, Audio Processing, Foundation Models
Deliverable
production ML models
Required skills
Statistical learning theory, foundation model architectures, bridging theory and practice, data pipeline design, controlled experimental design, model optimization for hardware, open-source contributions, research publications
Preferred skills
Self-supervised learning, multimodal learning, hardware constraints knowledge, scalable systems design
Technologies
Neural audio codecs, generative models, embedding systems, latent recombination, multimodal speech-to-speech systems
Responsibilities
Build neural audio codecs for low bit-rate compression and high fidelity; Pioneer steerable generative models for human speech synthesis; Develop embedding systems to factorize codec latent space; Leverage latent recombination to generate synthetic audio data; Design model architectures and training schemes for cost-efficient training and real-time inference.
Seniority
Senior, hands-on IC
