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AI Furnace Temperature Anomaly Detection Engineer

Ethan Park

Full-time · Job · Chicago

About the role

Sensor data, industrial furnace logs, and a decade of unplanned shutdown records are the core of what we work with here. If that sounds like real-world data science, keep reading. You'll build anomaly detection models that catch abnormal furnace temperature patterns hours before they'd otherwise trigger a shutdown, working from historical sensor streams already flowing into our data lake. This role is on-site at our manufacturing analytics hub, working directly alongside plant engineers.

Responsibilities

  • Build anomaly detection models on streaming furnace sensor data
  • Own model validation against historical shutdown incidents
  • Partner with plant engineers to tune alert thresholds
  • Maintain the Spark-based pipeline feeding model inputs

Requirements

  • 3+ years applying ML to industrial or sensor data
  • Strong SQL and Python for large-scale data processing
  • Experience with Spark or similar distributed processing tools
  • Comfortable working on-site with plant operations teams

Benefits

  • On-site role with relocation support
  • Competitive salary + equity
  • Health and dental insurance
  • Safety and manufacturing site training provided

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Categories

data science & analytics MLOps & AI Infrastructure

Skills

python sql scikit-learn spark aws

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

data science & analytics MLOps & AI Infrastructure

Skills

python sql scikit-learn spark aws

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