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.
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
Skills Required
- 3+ years of experience in speech technology with hands-on TTS experience
- Hands-on experience with modern LLM-based TTS approaches such as VALL-E, CosyVoice, or XTTS
- Experience making TTS models production-ready, including stability, robustness, and inference efficiency
- Proficiency with deep learning frameworks, especially PyTorch
- Understanding of Transformers, diffusion or flow matching, neural audio codecs, and vocoders
- Understanding of streaming TTS constraints, including latency and chunked or incremental generation
- Knowledge of audio signal processing and TTS linguistics, including phonetics and text normalization
- Basic experience with speech data processing, including segmentation, alignment, and quality filtering
- Familiarity with TTS evaluation methods such as MOS and SBS
- Strong Python skills and solid software engineering practices
- Ability to independently explore new ideas and improve existing ML systems
- Bachelor's degree or higher in Computer Science or a related field, or equivalent experience
- English proficiency at B2 level or higher
- Experience with low-resource languages, including dataset creation and augmentation
- Experience designing recording scripts and specifications for TTS voice datasets
- MLOps or DataOps experience with MLflow, DVC, or similar experiment tracking tools
- C++ skills
- Publications in speech or machine learning venues
Acclaim AI Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Acclaim AI and has not been reviewed or approved by Acclaim AI.
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Parental & Family Support — Parental leave is explicitly listed on the company’s Wellfound profile. Feedback suggests family support is part of the baseline perks communicated publicly.
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Leave & Time Off Breadth — Generous vacation is highlighted on Wellfound. This points to broader time-off flexibility typical of startup-style packages.
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Wellbeing & Lifestyle Benefits — Professional development and company events are called out on Wellfound. These signals indicate investment in growth and team connection beyond core benefits.
Acclaim AI Insights
What We Do
Acclaim is a voice-first AI customer experience (CX) platform purpose-built for regulated industries including banking, fintech, healthcare, and insurance. It provides enterprises with goal-oriented AI agents that go beyond conversation to deliver agentic solutions that solve end-to-end business problems—orchestrating and executing complete customer workflows from outreach through resolution. Acclaim's solutions transform human-driven CX processes into AI-powered ones that are continuously learning and improving. Our platform helps organizations delight with human-quality conversations, accelerate revenue-driving interactions, and safeguard their data by maintaining strict compliance across every customer channel—creating more seamless customer experiences while improving the productivity and satisfaction of human agents. Built on a privacy-first architecture with on-premises or private cloud deployment, Acclaim ensures every interaction is secure, compliant, and delivers results that speak for themselves.
