MSL (Material Science Lab) Intern Data Scientist (ML Model Development & Full-Stack Integration)

About our group:

Material Science Laboratory provides service support analytical technique and scientific analysis for material, process, products on cleanliness, contamination, and failure analysis under Operation Quality and Analytic (OQ&A)

About the role - you will:

• Create human decision algorithm based on the expert engineer step-by-step decision making during the conclusion of defect, particle and contamination classification.
• Use machine learning methods and AI (Artificial Intelligent) to complement the human decision algorithm
• Design and train image classification models using labelled datasets
• Design and implement a full-stack dashboard for model deployment, monitoring, and validation
• Integrate backend services with frontend UI for real-time model performance tracking
• Collaborate with data scientists, engineers, and lab teams to align system requirements
• Ensure modular, scalable, and maintainable code for long-term sustainability
• Work with IT to set up the server system to achieve the desired processing power & speed
• Create and implement workflow for the automated image classification tool or systems
• Document the development process and provide training materials for end users
• Communicate status of projects and progress to supervisor
• Summarize accomplishment, issue and relevant assignment as supervisor required

About you:

• Excellent teamwork, leadership and coachability
• Fast learning, able to prioritize multiple tasks and work effectively in a dynamic environment.
• Proficiency in computer programming languages, Python, JavaScript, and C++.
• Fundamental of machine learning, especially image classification (CNNs, Transfer learning)
• Experience Python and ML Libraries (e.g. TensorFlow, PyTorch, Scikit-learn)
• Understanding of full-stack development (e.g. Node.js, Flask/Django, React).
• Familiar with RESR APIs, Docker, Git, Linux, computer network, cloud, database, and virtual machine
• Basic knowledge of MLOps and model lifecycle management
• Experience in the data preparation process, image processing, image classification, data center management, machine leaning and AI projects
• Strong coding skill in Python, JavaScript, and SQL
• Ability to pre-process data, train, evaluate, and optimize ML Models
• Ability to design intuitive dashboards for technical and non-technical users
• Degree/master's in data science, statistics, computer, software, or electrical-related field
• Capable of communicating in a complex technical knowledge with cross-functional team
• Effective communication and presentation skills
• Ability to effectively plan, control and take responsibility for group's results
• Able to prioritize multiple tasks, manage conflicting deadlines, and work effectively in a dynamic environment
• Fluent in both spoken and written English communication

Your experience includes:

• Project experience in ML Model development and deployment
• Exposure to cloud platforms (E.g., AWS, GCP, Azure)
• Experience with CI/CD pipelines and containerization tools
• Experience connecting frontend and backend components
• Good knowledge of IOT
• Having a good understanding of KNIME, Image Processing, MATLAB, Vision system, Data networking and coding

Location:

Korat, Thailand

Our Korat facility is our largest manufacturing site worldwide, with almost 20,000 employees. Here, our team produces cloud-based storage equipment, from individual storage components to finish drives. Our employees enjoy ample on-site parking as well as free shuttle vans and buses within the city of Korat, to and from Bangkok, and on the weekend to and from Khon Kaen University. At work you can grab a delicious breakfast, lunch, dinner or snacks at one of our 24-7 on-site canteens or coffee shop. We offer ping-pong, a running/walking trail, basketball and volleyball teams, and classes in our on-site fitness center. We also have many on-site events and opportunities to give back to the local community.

Location: Korat Thailand
Travel: None