Data Scientist

Our Team

Micron’s Engineering Tool Development (ETD) group develops advanced software solutions that enable innovation across Micron’s technology development and manufacturing organizations. The team works at the intersection of software engineering, computer vision, and semiconductor technology to deliver tools that improve efficiency, yield, and insight across a broad range of engineering disciplines.

Job Summary

As a Computer Vision Engineer, you will apply computer vision, image processing, and machine learning techniques to solve complex software problems. You will work with multiple programming languages, frameworks, and disciplines, and you will be encouraged to experiment with new technologies while continuously developing your skills in a fast‑evolving technical environment.

As an engineer in the Engineering Tool Development group, you will have the opportunity to work on a broad set of technologies and solutions that enable Micron’s innovation across technology development and manufacturing.

Key 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 directly 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.

Required Qualifications

A Bachelor’s degree or equivalent experience in Computer Science, Computer Engineering, Mathematics, Statistics, or a related analytical field is required. Additionally, at least 2 years of relevant experience as a data scientist is needed.

Master’s degree in a relevant technical field plus a minimum of 2 years of relevant experience in a data scientist role.

Advanced degrees (M.S. or Ph.D.) with applied research or industry‑relevant experience are preferred.

Minimum of 4 years’ hands‑on experience proven ability to apply image processing techniques (e.g., filtering, morphology, segmentation), visual recognition methods (e.g., feature detection, measurement, classification), and machine learning approaches (spanning established algorithms and contemporary deep network techniques) for practical applications in engineering.

Proficiency in at least one primary programming language used for production of research workflows(e.g. Python, MATLAB, R) with proven ability to write maintainable, well-structured code.

Practical experience using computer vision libraries such as OpenCV and Scikit image(skimage) to solve real world image analysis problems.

Minimum 2 years working 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.

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.