Job Description

What you'll do

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Lead research on

Text-to-Speech models

focused on naturalness, expressiveness, latency, and robustness Design and train TTS systems for

real-world voices

across accents, languages, and speaking styles Improve

streaming and low-latency speech synthesis

pipelines Experiment with architectures, loss functions, and data strategies (multi-speaker training, style modeling, distillation, data augmentation) Translate research ideas into

production-ready TTS systems

Collaborate closely with infra, product, and voice engineering teams

What we're looking for

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Strong background in

Text-to-Speech / speech generation research

Hands-on experience with deep learning frameworks (

PyTorch preferred

) Experience with

real-time or low-latency TTS systems

Familiarity with modern TTS architectures (Tacotron-style, FastSpeech, VITS, diffusion-based, neural vocoders) Ability to think end-to-end:

data model inference deployment

Prior work in

multilingual, expressive, or accented speech synthesis

is a strong plus

Great to have

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Publications in top speech / ML conferences Experience deploying

TTS models in real-time production

Exposure to

conversational AI or voice agents

Years of Experience

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3-6 years

of specialized experience in speech through academia or industry

Education

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Master's or PhD in Speech, ML, or a related field

Note:

We often make exceptions and hire brilliant candidates regardless of years of experience or education.

Proof of work is paramount.

Compensation Range: $60K - $100K