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AI Compressor Health Monitoring Engineer

Ethan Park

Full-time · Job · Chicago

About the role

You'll be the third ML engineer on a team of twelve, working directly with the plant reliability engineers who currently rely on scheduled inspections to catch compressor failures. Our clients include manufacturers running compressors around the clock, and an unplanned failure can shut down an entire line for a full shift. You'll build a monitoring model that flags early degradation from vibration and temperature sensor data, giving maintenance teams days of warning instead of hours. This is an on-site role since you'll need direct access to the plant floor sensor network during rollout.

Responsibilities

  • Build early-warning models for compressor degradation from sensor data
  • Validate alerts against maintenance team ground-truth failure logs
  • Work on-site with plant engineers during initial sensor rollout

Requirements

  • 3+ years working with industrial sensor or time-series data
  • Comfortable with scikit-learn and statistical anomaly detection
  • Willing to work on-site at the manufacturing facility

Benefits

  • Competitive salary and annual bonus
  • Health and dental insurance
  • On-site cafeteria and gym access
  • Relocation assistance available

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Categories

AI & Machine Learning Engineers Automation & AI Workflows

Skills

python scikit-learn pandas statistics azure

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

AI & Machine Learning Engineers Automation & AI Workflows

Skills

python scikit-learn pandas statistics azure

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