Research Staff, Voice AI Foundations

• Pioneer Latent Space Models to address fundamental data, scale, and cost challenges in robust, contextualized voice AI
• Build next-generation neural audio codecs with extreme low-bit-rate compression and high-fidelity reconstruction
• Develop steerable generative models synthesizing diverse human speech, including emotional, multi-speaker, noisy, and overlapping-speech scenarios
• Create embedding systems that factorize latent spaces into speaker, content, style, environment, and channel dimensions
• Use latent recombination to generate synthetic audio data at previously impossible scales
• Train multimodal speech-to-speech systems for universal understanding and empathic, human-like responses
• Design model architectures, training schemes, and inference algorithms optimized for bare-metal hardware
• Enable cost-efficient training on billion-hour datasets and real-time inference for hundreds of millions of concurrent conversations
• Conduct rigorous controlled experiments, ablations, evaluations, and stress tests
• Collaborate through research publications and open-source contributions

• Strong mathematical foundation in statistical learning theory, particularly for self-supervised and multimodal learning
• Deep expertise in foundation model architectures and scaling training across multiple modalities
• Ability to derive novel mathematical formulations and implement them efficiently
• Demonstrated ability to build and maintain massive, high-quality, diverse data pipelines
• Experience designing controlled experiments to isolate architectural impacts and validate theoretical insights
• Experience optimizing models for real-world deployment, including hardware constraints and efficiency techniques
• Track record of open-source contributions or research publications advancing speech/language AI
• Ability to identify critical experiments that validate or disprove ideas quickly
• Vision to scale successful proofs-of-concept 100x
• Strong AI automation and augmentation mindset
• Scholarly literature or academic publications related to speech processing, STT/TTS, or similar requested in the application
• Legal authorization to work in the country where the role is located
• Ability to address visa sponsorship requirements for the country where the role is located

• Remote work arrangement
• AI-first work environment with opportunities to use and experiment with advanced AI tools
• Opportunity to work on transformative voice AI research
• Opportunity to contribute to open-source projects and research publications
• AI Notetaker interview recording is optional; opting out does not impact candidacy