Hiring nowSpeech, audio and music intelligence

Speech Synthesis Researcher

Also called TTS Scientist

A speech synthesis researcher builds text-to-speech models that sound natural, stay intelligible and respect speaker consent. Companies need them to ship voices people trust and to keep misuse in check.

What they do

The work starts with a voice problem: a product needs speech that is clear, expressive and controllable. The researcher designs and trains text-to-speech models, choosing data, architecture and conditioning for things like pace, emphasis and style. They run listening studies, set up objective checks for intelligibility, and compare systems against a baseline. They work with linguists on pronunciation and language coverage. They also build safeguards: consent records for every voice, limits on cloning, and ways to detect or trace synthetic audio.

What a strong hire delivers

In the first months, a strong hire produces a working speech model that the team can hear and test. They set up an evaluation routine covering intelligibility and perceptual quality, with a listening study that stands up to scrutiny. They document how speaker consent is recorded and enforced. They also leave the team with clear misuse controls and a shortlist of the next improvements.

How you can tell they are good

Ask them to walk through a voice system they built and how they knew it was good. Strong people describe their listening study design, how they chose listeners and stimuli, and where automatic metrics misled them. They talk about consent and misuse without being prompted. Be wary of anyone who relies on one score or says quality is obvious by ear.

Why it is hard to fill

Few people have done both the modelling and the evaluation well. Titles vary: TTS scientist, speech researcher, audio ML engineer. Many candidates come from acoustics, linguistics or music technology rather than machine learning. Most good ones are in research teams and are rarely looking. Consent and misuse experience is rarer still, so expect to assess it directly.

Where to find them

Look in speech processing groups, university phonetics and acoustics labs, and music technology programmes. Strong candidates hold titles such as speech scientist, TTS researcher, audio ML researcher or research engineer. They work at frontier labs, voice product companies, assistive technology firms, game and media studios, and large platform speech teams. Some move across from speech recognition work.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for a Speech Synthesis Researcher

Tell us about a speech synthesis model you shipped or published. What did you change that people could actually hear?
A strong answer names a specific problem, such as prosody or stability, and the change that fixed it. They separate their own contribution from the team's. Worry if they only cite metrics and cannot describe how the audio sounded.
How would you design a listening study to compare two voice models?
Look for clear test choice, such as preference or opinion scores, a sensible listener pool, varied text, controls and attention checks, and a plan for statistics. Worry about small samples, no baseline, or relying only on automatic scores.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are building speech products that need natural, controllable voices people can trust. We are looking for a speech synthesis researcher to design, train and evaluate text-to-speech models, and to make sure every voice we produce is consented, measured and protected against misuse.

What you will do

Design and train text-to-speech models with controllable style and pace
Run listening studies and report intelligibility and perceptual quality
Build objective evaluation that tracks what listeners hear
Work with linguists on pronunciation and language coverage
Implement speaker consent records and misuse controls
Document findings and share them with the wider team

What you will bring

Shipped or published text-to-speech or voice models you can walk us through
Experience designing and analysing listening tests
Strong deep learning skills, including work with Transformers
Practical use of audio toolchains and speech data pipelines
Clear thinking about consent, impersonation and misuse
Ability to explain results to non-specialists

Nice to have

Experience with multilingual or low-resource voices
Background in phonetics, acoustics or music technology
Work on synthetic speech detection or watermarking

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

Speech and audio modellingAdvancedRecognise, synthesise or analyse audio
Deep learningAdvancedBuild and diagnose trainable neural models
Linguistics and localisationWorkingAdapt language behaviour across cultural and linguistic contexts
Model evaluationWorkingMeasure capability and failure modes credibly

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

Generative AI: Navigating intellectual property, World Intellectual Property Organization
Transformers documentation, Hugging Face

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