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AI Multilingual Speech Synthesis Engineer

Elena Cohen

Full-time · Job · Berlin

About the role

We publish internally and encourage conference submissions. The person in this role will be expected to stay current with TTS research, implement findings that show promise, and contribute to a growing body of internal research on cross-lingual voice quality. We don't just want someone who can train models — we want someone who pushes the state of the art. Our speech synthesis platform supports 28 languages. The quality gap between English and our lower-resource languages — Swahili, Bengali, Tamil — is measurable and embarrassing. Native speakers in our user research sessions consistently rate non-English voices as robotic while English voices score near human-level. Closing that gap requires more than data collection: it requires architectural innovations in cross-lingual transfer and low-resource adaptation. You'll lead the multilingual quality initiative: designing transfer learning strategies, building evaluation pipelines with native-speaker-calibrated MOS metrics, and shipping improvements on a 6-week release cadence. You'll mentor one junior researcher and report to our Head of Speech AI.

Responsibilities

  • Design cross-lingual transfer learning strategies for low-resource TTS languages
  • Build MOS evaluation pipelines with native-speaker-calibrated quality metrics
  • Implement and evaluate recent research in low-resource speech synthesis
  • Develop phoneme alignment and prosody modeling improvements for 28 languages
  • Ship quality improvements on a 6-week release cadence
  • Publish research findings internally and externally at speech conferences

Requirements

  • 6+ years in speech synthesis, TTS, or related audio ML research
  • Deep expertise in neural TTS architectures: Tacotron, VITS, or equivalent
  • Publication record or significant open-source contributions in speech AI
  • Strong PyTorch skills and experience with cross-lingual transfer techniques
  • Experience with low-resource language model adaptation

Benefits

  • Fully remote across European time zones
  • Conference budget with no cap
  • 30 days PTO plus local holidays
  • Equity participation
  • Home lab equipment allowance

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Categories

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch hugging face docker aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch hugging face docker aws fastapi

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