Research Staff, Voice AI Foundations
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, Deep Learning
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 deployment, open-source contributions, research publications
Preferred skills
self-supervised learning, multimodal learning, hardware constraints knowledge, scalable training paradigms
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; Pioneer steerable generative models for speech synthesis; Develop embedding systems for latent space factorization; Leverage latent recombination for synthetic audio generation; Design model architectures and inference algorithms for hardware efficiency.
Seniority
Senior, hands-on IC