Manufacturing Engineer – Data Science
Core
Deploy AI and predictive models to improve yield, reduce defects, and minimize equipment downtime in AlMg Substrate manufacturing processes.
Role type
Manufacturing Engineer specializing in Data Science and AI/ML
Builds
Production ML models, analytics pipelines, and self-serve dashboards for manufacturing monitoring
Domain
Semiconductor/Storage manufacturing (AlMg Substrate) + Industrial AI/ML
Deliverable
production ML models | dashboards & analysis
Required skills
Machine learning algorithms (supervised, unsupervised, reinforcement learning), Statistical modeling (SPC, DOE, Cpk, multivariate analysis), Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch), SQL, Time-series analysis, Anomaly detection, MLOps practices
Preferred skills
Experience with smart manufacturing initiatives, Time-series analysis, Anomaly detection, Predictive maintenance modeling, Industrial IoT (IIoT) environments, Cloud platforms (Azure, AWS, GCP)
Technologies
Python, TensorFlow, PyTorch, Spotfire, SQL, Azure, AWS, GCP
Responsibilities
Identify and deploy AI use cases for yield improvement and defect reduction; Build predictive models using internal AI tools on MES/ERP/IoT data; Develop end-to-end analytics pipelines from extraction to deployment; Create dashboards for real-time Cpk, Yield, and SPC monitoring; Support AI-driven root cause analysis for quality excursions; Collaborate with Process, Quality, and Metrology teams to integrate analytics
Seniority
Early Career (Entry-level with Master's degree)