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AI Vocabulary Review Scheduling Engineer

John Mueller

Full-time · Job · Madrid

About the role

Learners in over 30 countries rely on our app daily, but right now every learner sees the same fixed review schedule regardless of how well they actually remember a given word. Our team already ships strong pronunciation and grammar feedback tools. What's missing is a model that predicts, per learner and per word, when forgetting is likely to happen so we can time review prompts before that word slips away. We believe language learning should be accessible everywhere, and that means our models need to work reliably across skill levels and learning paces, not just for fast learners.

Responsibilities

  • Build models that predict per-learner, per-word forgetting curves
  • Design a review scheduling system that adapts to individual retention
  • Validate scheduling accuracy against real learner retention data
  • Work with Hugging Face models for learner interaction feature extraction
  • Collaborate with education leads to define what a good schedule feels like

Requirements

  • 2+ years of experience with applied ML on behavioral or interaction data
  • Experience with PyTorch and Hugging Face libraries
  • Familiarity with spaced repetition or education technology a plus
  • Comfortable working with large-scale learner interaction datasets
  • Strong statistics background for retention modeling

Benefits

  • Hybrid role, one day per week in our Madrid office
  • Health insurance coverage
  • Language learning subscription for personal use
  • Professional development budget
  • Collaborative, mission-driven team culture

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

NLP & Prompt Engineering

Skills

python pytorch hugging face statistics

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