
Application Development Intern (Based Bangpu plant Samutprakarn)
- Samut Prakan
- Training
- Full-time
- Develop and implement custom applications, scripts, or digital tools (e.g., using Python, JavaScript, Google Apps Script, C#) to address specific needs on the production floor.
- Collaborate directly with shop floor personnel to understand operational processes, gather requirements, and ensure developed solutions are user-friendly and effective.
- Design and build solutions for data collection, analysis, and visualization from production equipment or manual inputs to provide real-time insights (e.g., OEE tracking, defect logging, material tracking).
- Test, debug, and refine applications in a live production environment, ensuring reliability and performance.
- Create and maintain clear documentation for all developed applications, including user manuals and technical specifications.
- Currently pursuing a Bachelor's Degree in Computer Science , Software Engineering ,Information Technology (IT) , Computer Engineering , Data Science, Artificial Intelligence, or Applied Mathematics/Statistics
- Prefer minimum 4 months internship and able based at Bangpu plant Samutprakarn
- Intership monthly applownce at 8,000 THB
- ( Priority #1 ) A. Core Web Development & Architecture (must ) :
- 1. JavaScript Frameworks (Frontend): Proficiency in React.js, Vue.js, or Angular.js for building dynamic user interfaces.
- 2. Frontend-Backend Architecture (REST API): Strong understanding of how client-side applications communicate with server-side services.
- 3. MVC Framework: Experience with the Model-View-Controller architectural pattern for structuring web applications.
- 4. ASP.NET Core (C#): Expertise in building robust and scalable backend services and APIs.
- 5. SQL (SQL Server preferred): Strong command of relational databases for data storage, retrieval, and management.
- 6. Version Control (Git & GitHub): Essential for collaborative software development, code management, and deployment workflows.
- (Priority#2)
- 7. Python (Notebook or Scripting): Crucial for data manipulation, machine learning model development, prototyping, and automation. This skill becomes even more central with the AI focus.
- 8. Generative AI / AI Concepts:
- Machine Learning Fundamentals: Understanding of supervised, unsupervised learning, model training, evaluation metrics.
- Deep Learning Basics: Knowledge of neural networks and their applications (e.g., for generative models).
- Generative AI Models: Familiarity with concepts like Large Language Models (LLMs), GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and their application areas.
- AI Model Deployment: Understanding how to integrate trained AI models into web applications (e.g., via APIs), often using cloud services.
- Data Preprocessing & Feature Engineering: Skills in preparing data for AI models.
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