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Hadrian

Manufacturing Data & Process AI Integration System Engineer, Additive Manufacturing

Los Angeles, CA$135k–$220kfulltimemidAdded today

About this role

Hadrian seeks a Manufacturing Data & Process AI Integration System Engineer to own the monitoring, analytics, and AI/ML modeling layer for their additive manufacturing fleet. You'll develop predictive models for build quality and process anomalies, build data infrastructure, create real-time dashboards, and drive closed-loop integration between AI predictions and production workflows.

What you'll do

  • Own monitoring and analytics layer for AM fleet, defining what's computed, surfaced, and alerted on
  • Develop and deploy AI/ML models to predict build quality, detect anomalies, and optimize process parameters
  • Build feature engineering infrastructure, data quality checks, labeling workflows, model versioning, and performance tracking
  • Create process monitoring dashboards and AI-driven alerts for real-time machine and build health visibility
  • Integrate model outputs back into manufacturing workflow to drive closed-loop actions and parameter adjustments
  • Apply statistical process control to AM data, establish control limits, and detect process drift

What they're looking for

  • Python and ML frameworks (scikit-learn, TensorFlow, PyTorch)
  • SQL and time-series manufacturing data handling
  • AI/ML model development, training, validation, and production deployment
  • Statistical process control and structured problem-solving (8D, 5 Whys, fishbone)
  • Manufacturing process engineering and data systems
  • Dashboard and analytics visualization development
  • Metal additive manufacturing domain knowledge
  • MLOps practices and model monitoring

Benefits

  • Medical, dental, vision, and life insurance
  • 401k retirement plan
  • Equity
  • Flexible vacation policy
  • Potential relocation support
  • Full-time on-site role with meaningful aerospace and defense impact
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Hadrian

Hadrian builds aerospace and defense manufacturing systems, offering enterprise software platforms, advanced tooling design, and highly automated production capabilities for the sector. The company is hiring full stack engineers, manufacturing and tooling specialists, infrastructure and identity management experts, and workforce systems architects to support its rapid scaling.

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Likely interview questions

  • Walk us through a time you developed and deployed an ML model in a production manufacturing environment—what were the key challenges and how did you validate it before full deployment?
  • Describe your experience building analytical datasets from raw manufacturing sensor data. How have you handled missing data, resampling, and quality issues at scale?