MSL (Material Science Lab) Intern Data Scientist (ML Model Development & Full-Stack Integration)
Reads like a ML Engineer role: putting models into production.
Nakhon Ratchasima, TH
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign and train image classification models on labelled datasets
Turn expert engineers' decision steps into a human decision algorithm
Design and implement a full-stack dashboard for model deployment and monitoring
Integrate backend services with frontend UI for real-time model performance tracking
Create and implement workflow for the automated image classification tool
From the employer’s posting
Design and train image classification models using labelled datasets
Create human decision algorithm based on the expert engineer step-by-step decision making
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
Create and implement workflow for the automated image classification tool or systems
What you’ll bring
All qualificationsCore experience
- Proficiency in computer programming languages, Python, JavaScript, and C++.
- Experience in the data preparation process, image processing, image classification, data center management, machine leaning and AI projects
- Ability to effectively plan, control and take responsibility for group's results
- Experience with CI/CD pipelines and containerization tools
- Experience Python and ML Libraries (e.g.
- Ability to pre-process data, train, evaluate, and optimize ML Models
Qualification wording
Proficiency in computer programming languages, Python, JavaScript, and C++.
Experience in the data preparation process, image processing, image classification, data center management, machine leaning and AI projects
Ability to effectively plan, control and take responsibility for group's results
Experience with CI/CD pipelines and containerization tools
Experience Python and ML Libraries (e.g. TensorFlow, PyTorch, Scikit-learn)
Ability to pre-process data, train, evaluate, and optimize ML Models
Education & alternatives
- 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
Tools in this posting
- C++
- JavaScript
- MATLAB
- Python
- SQL
- AWS
- Azure
- Docker
- GCP
- Django
- Flask
- PyTorch
- React
- scikit-learn
- TensorFlow
- Node.js
Source — Tool mentions in context
- 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 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
- Good knowledge of IOT - Having a good understanding of KNIME, Image Processing, MATLAB, Vision system, Data networking and coding Location:
- 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).
- 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
- 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 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
About Seagate Technology
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)
In the employer’s words · Read in context
Posting record
Report an errorOpen 4 monthsWe first saw this posting 136 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 15, 2026 · 136 days ago
- Recorded sightings
- 496
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on seagatecareers.com. The employer’s form will show what is required.
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Job description
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:
About you:
Your experience includes:
Location:
Location: Korat Thailand
Travel: None
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Nakhon Ratchasima, TH
Korat, Thailand Our Korat facility is our largest manufacturing site worldwide, Here, our team produces cloud-based storage equipment, from individual storage components to finished drives. Employees enjoy ample on-site parking, free shuttle vans and buses within the city of Korat, as well as transportation to and from Bangkok and Khon Kaen province on weekends. At work, you can grab a delicious breakfast, lunch, dinner, or snacks at one of our 24/7 on-site canteens or coffee shops. We offer table tennis, basketball, volleyball, a running/walking trail, and exercise classes in our on-site fitness center. In addition, there are relaxing spaces with comfortable seating both indoors and outdoors, perfect for taking a break during the day. Additionally, consider joining any of our employee resource groups (ERGs), such as Seagate Women in Leadership Network (SWLN), Seagate PRIDE: Thailand chapter, or Seagate Asia’s parents and caregivers group. We also have many on-site recreation events and opportunities to give back to the local community. Location: Korat Thailand
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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