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Position
AI/ML Solution Developer - FD and FP Focus with APC (R2R) Support
Description
The Automation Products Group in Applied Global Services is seeking a forward-thinking AI/ML Application Development Engineer with a primary focus on Fault Detection (FD) and Fault Prediction (FP) solutions and a secondary focus on Run-to-Run (R2R) / Advanced Process Control (APC). In this role, you will design, develop, test, and deploy high-performance FD and R2R models that integrate seamlessly with semiconductor manufacturing processes. By leveraging artificial intelligence (AI) and machine learning (ML), you will help create solutions that enable process/equipment anomaly detection, chamber matching, automated windowing, early detection of failures (parts, equipment), trace-level data FP and FD, and process shift identification. You will leverage data science (DS) skills to lead the deployment of AI FD/R2R solutions and collaborate with customers to develop successful case studies of AI applications using their data.
You will collaborate closely with cross-functional teams-including process engineers, product managers, and analytics experts-to provide efficient, accurate, and scalable FD/R2R applications. Responsibilities include engaging in pre-sales activities, delivering technical presentations, supporting system integration efforts, and participating in continuous improvement initiatives to optimize manufacturing processes.
Additional responsibilities include involvement in presales and deployment activities. These responsibilities are as follows:
FD AI/ML Model Design and Development (main role)
R2R Controller & AI/ML Model Design and Development (secondary role)
Deployment and System Integration
Pre-sales Support & Customer Relationship Management
Continuous Optimization & Technology Exploration
Act as a consultant to define working tasks and project scope for new customers seeking FD/FP and R2R services.
Manage FD/FP and R2R projects or consolidate contracts of work if necessary.
Preferred Knowledge and Experience
Operational knowledge of typical factory automation and equipment/process fault analysis and R2R control systems.
Additional understanding of MES, Dispatching, Scheduling, SPC, FDC, AMHS, Equipment Integration, general information technology, and database technology is a plus.
Proficiency in Python and C#, with experience using machine learning and deep learning frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
Strong knowledge of data science workflows, including data preprocessing, feature engineering, model development, evaluation, and deployment.
Experience with data science is a plus.
Hands-on experience in building and applying Virtual Metrology models using Neural Networks or other regression/classification methods for measurement prediction is a plus
Expertise in statistical and multivariate analysis, including SPC, FDC, and other analytical tools is a plus.
Ability to collaborate effectively with customers, technical teams, project managers, and stakeholders, ensuring high-quality and timely project delivery.
Prior experience as a Project Manager (PM) or Technical Lead is a plus.
Experience with Smart Factory or Industry 4.0 AI/ML model implementations is a plus.
Experience with software development business processes is a plus
Direct experience using SmartFactory E3 FDC/R2R is a plus.
Qualifications and Education
Bachelor's degree in engineering or computer science & Master's degree in data science or AIML specialization
Strong written and verbal communication skills.
Knowledge of the semiconductor manufacturing business.
Proficiency in English and Chinese.
Applied Materials is committed to diversity in its workforce including Equal Employment Opportunity for Minorities, Females, Protected Veterans and Individuals with Disabilities.
Additional Information
Time Type:
Full time
Employee Type:
Assignee / Regular
Travel:
Yes, 25% of the Time
Relocation Eligible:
No
Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.