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Junior AI Production Yield Root Cause Analysis Developer

Ethan Park

Full-time · Job · Detroit

About the role

When production yield drops from 96% to 91% on a manufacturing line, engineers need to find the root cause before more defective units ship. The data exists — sensor readings, material lot metadata, operator shift records, maintenance logs — but it's spread across four different systems and it takes a senior process engineer 3-4 hours to manually correlate it into a hypothesis. That delay is expensive. Our industrial AI platform serves 22 manufacturing clients with digital twin and predictive analytics capabilities. Root cause analysis automation is the next feature on the roadmap: given a production yield degradation event, automatically correlate sensor data, material metadata, and operational records to surface the most likely contributing factors ranked by statistical evidence strength. As a junior developer, you'll help build the data integration and correlation pipeline. Senior engineers define the statistical methodology; you'll build the ETL pipelines that aggregate the multi-source data into a unified timeline, implement the correlation computation for pre-identified root cause feature types, and create the root cause reports that process engineers review. Real manufacturing data, real process engineers who'll tell you when the output is useful, real improvement in how fast problems get solved.

Responsibilities

  • Build ETL pipelines aggregating sensor, material, operator, and maintenance data into unified event timelines
  • Implement correlation computation between yield degradation events and candidate root cause features
  • Create root cause analysis reports ranking contributing factors by statistical evidence strength
  • Build data quality checks ensuring pipeline completeness before analysis triggers
  • Develop yield event detection alerting the analysis pipeline when degradation thresholds are crossed
  • Document pipeline architecture and correlation methodology for client process engineering teams

Requirements

  • 1+ year of Python and SQL development experience
  • Basic familiarity with data pipelines and time-series data concepts
  • Interest in manufacturing, industrial IoT, or operations analytics
  • Attention to detail in correlation analysis and report accuracy
  • Good communication skills for collaborating with process engineers

Benefits

  • Fully remote with flexible schedule
  • Health and dental insurance
  • $1,500 annual learning budget
  • Mentorship from senior industrial AI engineers
  • 401(k) with match

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Categories

MLOps & AI Infrastructure Automation & AI Workflows

Skills

python sql pandas airflow docker

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Job Type

Full-time

Level

Junior

Language

English

Salary Range

$60k – $80k / year

AI Expertise

MLOps & AI Infrastructure Automation & AI Workflows

Skills

python sql pandas airflow docker statistics

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