Senior/Staff, Data Scientist

1100 Micron SemiAsiaOP Pte Ltd; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

1100 Micron SemiAsiaOP Pte Ltd in Singapore is seeking a skilled engineer to design advanced image processing and analysis solutions. The role involves applying computer vision and machine learning techniques to enhance engineering efficiency across Micron's technology. A Bachelor's or Master's degree with a minimum of 4 years of experience is required, and proficiency in programming is essential.

The ideal candidate will collaborate in a global team environment, focusing on continuous improvement and providing support during critical incidents. This is an exciting opportunity to contribute to innovative semiconductor technology development.

Qualifications

• 4+ years of hands-on experience applying image processing techniques.
• Proficiency in programming languages like Python, MATLAB, or R.
• 2+ years of experience with machine learning frameworks.

Responsibilities

• Design and develop image processing and analysis solutions.
• Apply computer vision techniques to solve engineering problems.
• Collaborate with engineers in various diagnostic domains.

Skills

Image processing techniques

Machine learning

Python

OpenCV

Deep learning models

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

MATLAB

TensorFlow

Keras

Job description

The ETD group works at the intersection of software engineering, computer vision, and semiconductor technology to deliver tools that improve engineering efficiency and insight across Micron’s technology development and manufacturing organizations.

Responsibilities

• Design and develop advanced image processing and analysis solutions to extract measurements, perform calculations, and analyze image data.
• Apply computer vision, image processing, and machine learning techniques to solve practical engineering problems.
• Collaborate with engineers in defect analysis, electrical failure analysis, process development, and other diagnostic domains.
• Develop solutions that improve engineering efficiency and enable innovation using modern software and vision technologies.
• Work within a global team environment and contribute to continuous improvement and technical learning.
• Assist with rotational on‑call support, providing engineering‑level assistance during critical manufacturing incidents or system outages as needed.

Qualifications

• Bachelor’s or Master’s degree (or equivalent experience) in Computer Science, Computer Engineering, Mathematics, Statistics, or a related analytical field.
• Advanced degrees (M.S. or Ph.D.) with applied research or industry‑relevant experience preferred.
• Minimum of 4 years of hands‑on experience applying image processing techniques (e.g., filtering, morphology, segmentation), visual recognition methods (e.g., feature detection, measurement, classification), and machine learning approaches for practical engineering applications.
• Proficiency in at least one primary programming language used for production workflows (e.g., Python, MATLAB, R) with ability to write maintainable, well‑structured code.
• Experience using computer vision libraries such as OpenCV and Scikit‑image (skimage) to solve real‑world image analysis problems.
• Minimum 2 years of experience developing, training, and validating machine learning and/or deep learning models using frameworks such as PyTorch, TensorFlow, or Keras.
• Customer focus and relationship‑building skills.
• Proven ability to drive results and continuous improvement.
• Excellent foundation in mathematics, probability theory, machine learning, and computer vision.
• Basic knowledge of professional software engineering practices.
• Knowledge of semiconductor manufacturing processes is preferred.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

To request assistance with the application process and/or for reasonable accommodations, please contact [e-mail].