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AI Injury Risk Prediction Engineer

Trivon Data

Remote · $130k – $160k / year · Full-time · Posted 4 months ago

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About the role

Professional sports teams spend $180M per year on player salaries and lose an average of $22M annually to preventable soft-tissue injuries. The research shows that injury risk is predictable — but only if you're combining workload metrics, biomechanical data, and recovery indicators in the right way. Most teams aren't. We're building the injury prediction platform used by 14 professional teams across the NFL, NBA, and Premier League. Our current model achieves 73% recall on high-risk injury events 7 days out. The ceiling is higher. You'll redesign the feature engineering layer to incorporate GPS tracking data, sleep and HRV recovery metrics, and historical injury patterns in ways our current model ignores. You'll work alongside sports scientists who understand the physiology and data engineers who handle the sensor pipelines. If you've ever wanted your ML work to have a clear human impact — keeping athletes healthy and on the field — this is that role.

Fully remote.

Responsibilities

  • Redesign feature engineering for injury prediction using GPS, HRV, and workload data
  • Improve model recall on high-risk injury events at 7-day prediction horizon
  • Build individual athlete baseline models that detect deviation from personal norms
  • Design evaluation frameworks that account for class imbalance in rare injury events
  • Collaborate with sports scientists to encode physiological domain knowledge
  • Deploy models into the coaching staff dashboard used during daily team sessions

Requirements

  • 5+ years in ML engineering with time series or sports science experience
  • Experience with imbalanced classification and survival analysis
  • Strong Python and statistical computing skills
  • Ability to work with small, high-value labeled datasets
  • Track record deploying models in real-time operational environments

Benefits

  • Fully remote
  • Health, dental, and vision
  • $5,000 annual learning budget
  • Access to proprietary professional sports datasets
  • Equity package

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Categories

AI & Machine Learning Engineers Data Science & Analytics

Skills

python pytorch scikit-learn pandas statistics

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$130k – $160k / year

AI Expertise

AI & Machine Learning Engineers Data Science & Analytics

Skills

python pytorch scikit-learn pandas statistics sql

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