Research Staff, Voice AI Foundations

The Opportunity

Voice is the most natural modality for human interaction with machines. Current sequence modeling paradigms cannot deliver voice AI capable of universal human interaction due to fundamental data problems in audio. New paradigms for audio AI are needed to overcome these challenges.

The Role

As a Member of the Research Staff, you will pioneer the development of Latent Space Models (LSMs) to solve data, scale, and cost challenges in voice AI. Focus areas include:

• Build next-generation neural audio codecs for extreme low bit-rate compression and high fidelity reconstruction.
• Pioneer steerable generative models for synthesizing diverse human speech from codec latents.
• Develop embedding systems that factorize codec latent space into interpretable dimensions.
• Leverage latent recombination to generate synthetic audio data at scale for multimodal speech-to-speech systems.
• Design model architectures, training schemes, and inference algorithms optimized for hardware efficiency.

The Challenge

Seeking researchers who:

• See unsolved problems as opportunities to pioneer new approaches.
• Identify critical experiments quickly.
• Scale proofs-of-concept 100x.
• Use AI to automate and amplify impact.

It's Important to Us That You Have

• Strong mathematical foundation in statistical learning theory, particularly self-supervised and multimodal learning.
• Deep expertise in foundation model architectures and scaling across modalities.
• Proven ability to bridge theory and practice.
• Demonstrated ability to build data pipelines for massive datasets.
• Track record of designing controlled experiments.
• Experience optimizing models for deployment and hardware constraints.
• History of open-source contributions or research publications in speech/language AI.

Benefits & Perks

• Medical, dental, vision benefits.
• Unlimited PTO, generous parental leave, flexible schedule.
• 401(k) with company match.
• Learning/education stipend, conference participation.