Hadrian
Manufacturing Data & Process AI Integration System Engineer, Additive Manufacturing
$135K–$220K
Los Angeles, CA · On-site · Full-time · Posted Sep 26, 2026
- Experience
- 4+ years in manufacturing data systems, process engineering, or data-driven manufacturing in a production environment.
- Education
- Bachelor's degree in Manufacturing Engineering, Computer Science, Data Science, Materials Science, or related field.
- Visa sponsorship
- Must be a U.S. person for ITAR purposes: a U.S. citizen or national, lawful permanent resident, protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain required authorizations from the U.S. Department of State.
About the job
Develops and operates analytics and AI/ML systems for additive manufacturing, using machine and build data to predict quality, detect anomalies, and inform production decisions.
What you'll do
- Own curated manufacturing datasets, monitoring, analytics, dashboards, and alerting for the additive manufacturing fleet.
- Develop, deploy, and maintain AI/ML models and infrastructure for quality prediction, anomaly detection, and process optimization.
- Validate model outputs with engineering teams and support process control, qualification analysis, and corrective actions.
What they ask for
- Bachelor's degree in Manufacturing Engineering, Computer Science, Data Science, Materials Science, or a related field.
- 4+ years in manufacturing data systems, process engineering, or data-driven manufacturing in a production environment.
- Hands-on experience developing and deploying AI/ML models in an engineering or manufacturing context.
- Proficiency in Python, relevant ML frameworks, and SQL; experience building analytical datasets from manufacturing data.
Nice to have
- Experience applying AI/ML to metal additive manufacturing or working with in-situ process monitoring data.
- Experience supporting aerospace, defense, or regulated-manufacturing qualification data packages; MLOps or closed-loop process control experience.
Pay
$135K – $220K (base salary)
Tools
Python, scikit-learn, TensorFlow, PyTorch, SQL, OPUS, 8D, SPC
AI focus
Develop and deploy models for build-quality prediction, process-anomaly detection, and parameter optimization; build model infrastructure and integrate outputs into manufacturing workflows, working toward closed-loop parameter adjustment.
Model-written summary · the original posting is authoritative