> Markdown version of [/jobs/ext/2714964-machine-learning-scientist](https://www.wearedevelopers.com/jobs/ext/2714964-machine-learning-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Machine Learning Scientist

- **Company:** Voice AI Inc.
- **Location:** United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Codecs, Computational Linguistics, Distributed Computing Environment, Pytorch, Speech Synthesis, Front End Software Development
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/machine-learning-scientist-rime-labs-8299380

## About the Role

* Deep familiarity with the speech synthesis literature, contemporary and historical - Tacotron, FastSpeech, VITS, VALL-E, the codec-LM lineage. Opinions on what worked and why.
 * Hands-on training with neural codecs (EnCodec, DAC, Mimi, etc.) and multiple representation choices.
 * Experience with full- or half-duplex multi-modal modeling (Moshi, LLaMA-Omni, streaming S2S).
 * Strong attention to detail on data quality. You notice when an annotation pipeline is silently degrading or when an eval set has leakage.
 * Willing to roll up your sleeves on unglamorous data and training work - paired with the agency to build pipelines so the team isn't stuck doing it by hand.
 * Working knowledge of TTS frontend (G2P, normalization, prosody) and experience working with linguists.
 * Strong PyTorch fundamentals. Comfortable with training loops, distributed training, model internals.
 * PhD or equivalent research experience in speech, audio, ML, or computational linguistics or a track record that makes the credential irrelevant.

Nice to have

 * Multilingual TTS experience.
 * Background in prosody or paralinguistics.
 * Published work in speech, audio, or core ML venues.
 * Experience taking research models to production: quantization, distillation, streaming inference.

## Description

* Design, train, and evaluate speech synthesis models, autoregressive and non-autoregressive.
 * Drive research on full-duplex and half-duplex multi-modal architectures, including unified S2S systems.
 * Choose and iterate on speech representations: neural codecs, semantic tokens, mel features, continuous latents.
 * Build rigorous evaluation, objective and perceptual. Hold the bar on quality and prosodic control.
 * Collaborate with our linguists on TTS frontend behavior so modeling and frontend choices reinforce each other.


## Related Videos

- [Raise your voice!](https://www.wearedevelopers.com/videos/10-raise-your-voice)
- [Can You Touch the Internet? A Journey in Remote Touch With Edge Computing and Haptic Coding](https://www.wearedevelopers.com/videos/1463-can-you-touch-the-internet-a-journey-in-remote-touch-with-edge-computing-and-haptic-coding)
- [Building a Browser-Based Karaoke Game with Web Speech API](https://www.wearedevelopers.com/videos/1274-building-a-browser-based-karaoke-game-with-web-speech-api)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Speech-to-Speech AI models - Marius Obert](https://www.wearedevelopers.com/videos/1907-speech-to-speech-ai-models-marius-obert)
- [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models)

## Related Articles

- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [Clone Your Voice with ElevenLabs LLMs and Node](https://www.wearedevelopers.com/magazine/739-clone-your-voice-with-elevenlabs-llms-and-node)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this)
- [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)