We’re expanding our TTS to new languages and moving to next-generation LLM-based TTS, and we’re looking for a Machine Learning TTS Engineer to help bring these technologies to production quality! You’ll join a small TTS team of 2–3 ML engineers, supported by a dedicated MLOps team and a data engineer.

Requirements

- 3+ years of experience in speech technology with hands-on TTS experience.

- Hands-on experience with modern LLM-based TTS approaches (e.g., VALL-E, CosyVoice, XTTS).

- Experience making TTS models production-ready: stability, robustness, and inference efficiency at the model level.

- Proficiency in deep learning frameworks, especially PyTorch.

- Understanding of modern ML fundamentals: Transformers, diffusion/flow matching, neural audio codecs, and vocoders.

- Understanding of streaming TTS constraints (latency, chunked/incremental generation) and how they shape model architecture choices.

- Knowledge of audio signal processing and the linguistic side of TTS (phonetics, text normalization).

- Basic experience with speech data processing (segmentation, alignment, quality filtering).

- Familiarity with TTS evaluation methods (MOS, SBS).

- Strong Python skills and solid software engineering practices.

- Proven ability to independently explore new ideas and improve existing ML systems.

- BS or higher in Computer Science or a related field, or equivalent experience.

- English B2+.

Nice to have

- Experience with low-resource languages, including dataset creation and augmentation.

- Experience designing recording scripts and specs for TTS voice datasets.

- MLOps/DataOps experience, e.g.,



MLflow, DVC, or similar experiment tracking tools.

- C++ skills.

- Publications in speech/ML venues.

Responsibilities

Extend our TTS to new languages: data collection and curation, text normalization/G2P, and model adaptation.

Take new TTS architectures from research to production: improve robustness, latency, and quality, working closely with MLOps on deployment.

Push existing models further through post-training, data curation, architectural improvements, and new training approaches.

Build efficient audio data pipelines, from speaker recording and preprocessing to model training.

Design rigorous benchmarks and evaluations that show whether a new model iteration is genuinely better, and why.

What we offer

- The team has built award-winning AI products for tech corporations — devices, voice assistants, products that are actually in the world

- Cutting-edge tech stack: Speech Technologies, NLP, Generative AI (LLMs, diffusion models), voice-first agentic architecture with privacy-first and on-premises deployment

- High engineering bar and real ownership — the team cares about what actually works in production, not what looks good in a demo, and you'll see the impact of your work directly

- Fast career progression — a senior-heavy team and a high volume of real problems means you grow faster than you would anywhere else

- Startup pace with enterprise stability — real clients, real revenue, no bureaucracy

- Fully remote across Europe

- 21 vacation days + public holidays + 5 sick days

- Private English lessons via Preply

📌 Machine Learning TTS Engineer (Barcelona)
🏢 Acclaim AI
📍 Barcelona