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AI Pronunciation Error Feedback Developer

John Mueller

Full-time · Job · Berlin

About the role

"Your pronunciation was 73% accurate" is useless feedback. "You pronounced the /θ/ sound in 'think' as /t/ — try placing your tongue between your front teeth" is feedback a learner can act on. Our pronunciation feedback system moves beyond accuracy scores to generate phoneme-level explanations that teach learners exactly what to change and why. You'll build the feedback generation pipeline: acoustic feature extraction from learner recordings, phoneme-level comparison against native speaker references, articulation error classification by type (substitution, deletion, insertion, stress error), and natural language explanation generation that describes the error in terms a language learner understands — not in IPA notation, but in plain language about tongue position and airflow. The language learning AI team is five engineers. You'll work alongside an applied linguist who validates the pedagogical quality of generated feedback and audio engineers who maintain the acoustic reference models.

Responsibilities

  • Build phoneme-level pronunciation error detection from learner recordings
  • Classify articulation errors by type: substitution, deletion, stress errors
  • Generate plain-language feedback describing errors in learner-accessible terms
  • Evaluate feedback usefulness through learner improvement rates
  • Handle accent variation — distinguish foreign accent from error
  • Support 8 target languages with native speaker reference models

Requirements

  • 3+ years in speech ML with pronunciation or phonetics focus
  • Understanding of phonetics, phonology, and second language acquisition
  • Strong PyTorch skills for audio model development
  • Experience with speech-to-text or forced alignment tools
  • Ability to work with linguists and generate pedagogically appropriate feedback

Benefits

  • Fully remote across EU time zones
  • 30 days PTO
  • €2,500 learning and conference budget
  • Free language course access
  • Meaningful work improving language learning outcomes

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Categories

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch hugging face docker fastapi

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

AI & Machine Learning Engineers NLP & Prompt Engineering

Skills

python pytorch hugging face docker fastapi

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