Machine Learning TTS Engineer

Acclaim; United States; Remote; USD 130,000 - 195,000; Full time

Benefits offered by this job

Fully remote across Europe

21 vacation days + public holidays + 5

Private English lessons via Preply

Job summary

Acclaim ищет инженера по машинному обучению в области TTS для расширения на новые языки и перехода к продакшн‑уровню LLM‑основанных TTS‑систем. Вы присоединитесь к небольшой команде из 2–3 ML‑инженеров, поддерживаемой MLOps и дата‑инженером.

Задачи включают расширение данных, внедрение новых архитектур, оптимизацию задержки и качества, а также построение эффективных аудио‑пайплайнов и проведение надежных оценок изменений моделей.

Qualifications

• 3+ лет опыта в речи и TTS;Hands-on TTS опыт.
• Опыт современных LLM‑основанных TTS подходов (VALL‑E, CosyVoice, XTTS).
• Продакшн‑готовность: стабильность, устойчивость и эффективность вывода.
• Zнаделен/а опытом работы с PyTorch и ML‑инфраструктурой.
• Знание аудио сигнальных процессов и лингвистических основ TTS.

Responsibilities

• Расширение TTS на новые языки: сбор данных, нормализация текста.
• Перевод архитектур в продакшн: снижение задержек, повышение качества.
• Построение пайплайнов аудио‑данных и обучение моделей.
• Разработка и проведение упругих бенчмарков и оценок.

Skills

Python

C++

PyTorch

Transformers

English B2+

Education

BS or higher in Computer Science or related field

Tools

MLflow

DVC

PyTorch

Job description

Описание:

Description 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.

Задачи:

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.

Требования:

• 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+.
• 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.

Условия:

• 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