About the role
The Data and AI Solution Architect designs and implements advanced analytics and machine learning frameworks to optimize semiconductor manufacturing yield and operational efficiency. This role bridges complex manufacturing data environments with scalable cloud and edge AI solutions to drive predictive insights.
TechnologyOnsiteSolution Architecture
Key Responsibilities
- Design and deploy end-to-end data architectures for semiconductor manufacturing data including yield, metrology, and sensor logs
- Develop AI/ML models for predictive maintenance of fab equipment and manufacturing yield optimization
- Collaborate with process engineers to identify opportunities for automation and advanced process control improvements
- Establish data governance and security protocols for sensitive intellectual property and manufacturing process data
- Lead the integration of MES, ERP, and IoT sensor data into centralized high-performance data lakes
- Select and manage technology stacks involving cloud platforms like Azure or AWS and processing frameworks like Spark
- Mentor junior data scientists and engineers on best practices for industrial-grade AI deployment
- Translate business requirements into technical specifications for automated data pipelines and real-time dashboards
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, or a related engineering field
- Minimum 7 years of experience in data architecture or solution design for industrial applications
- Proven experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Strong proficiency in SQL and Python/R for complex data manipulation and statistical modeling
- Extensive experience with Big Data technologies including Spark, Hadoop, or Kafka
- Knowledge of semiconductor manufacturing processes or industrial automation standards like SEMI
- Familiarity with cloud infrastructure components on AWS, Azure, or GCP and MLOps practices
- Demonstrated ability to lead cross-functional technical projects and communicate with executive stakeholders
- Experience with data visualization tools such as Tableau, PowerBI, or Grafana
- Strong understanding of data security and compliance requirements in a manufacturing context