AFM ML Auto Image Statement Labeling project

Since 1979, Seagate has been creating precision-engineered data storage technologies that deliver superior capacity, speed, safety, and performance. We are a diverse workforce of 40,000 creative, hard-working, passionate people all over the world—Silicon Valley, the Southeast Asia, India, China, the United Kingdom, and beyond. At Seagate, we know that data is always in motion, alive, connected—and we harness it in order to maximize human potential. 

We are developing a machine learning (ML) solution to automatically review and label AFM (Atomic Force Microscopy) images. The goal is to design, build, and test a machine learning workflow that improves image quality checking, reduces rework, and standardizes image labeling. 

• Study the current AFM image review and labeling process 

• Collect, organize, and prepare AFM raw images for machine learning use 

• Assist in developing and training a machine learning model for image classification 

• Evaluate model performance and identify common failure cases 

• Support integration of ML results into the existing AFM data workflow 

• Create simple documentation and presentation materials to explain results 

• Self-motivated and independent learner 

• Team player with excellent communication and interpersonal skills 

• Resourceful and savvy professionals that are committed to finding solutions and making an impact 

• Good team player with stakeholder management skills 

• Strong interpersonal and communication skills (written and verbal) 

• Good in English verbal and written communication. 

• Detail-oriented and organized 

• Currently pursuing a bachelor’s degree in IT, Computer Science, Computer Engineering majors or a related field 

• Experience with image processing or machine learning projects 

• Familiarity with libraries such as TensorFlow, PyTorch, OpenCV or similar. 

• Interest in manufacturing, automation, or AI applications 

• Basic understanding of data visualization or reporting tools