Day to Day Responsibilities:
Plan, execute, and improve the M4.0 strategy. Lead digital projects implementations.
Develop, implement, and optimize digital solutions to support the digital transformation of manufacturing processes. including hardware and software systems.
Manage, query, and analyze databases to inform strategic decision-making and improve operational efficiency.
Testing and continuously improving the accuracy of machine learning models.
Provide constructive recommendation based on the data driven insights.
Collaborate with other engineers and other stakeholders to ensure that the digital solutions align with company objectives and customer needs.
Stay updated with emerging technologies, digital trends, and best practices in the manufacturing industry.
Establishes operation process and sustains daily performance, troubleshooting while performance upset or equipment shut down. Support equipment and control system improvement and develop the most efficient production technology. Design, modify, and recommend equipment types to meet or exceed requirements in operation.
Leads performance improvement project to achieve target goal. Such as yield, uptime, quality, lowest cost and equipment capability projects.
Implements and documents material, process and/or equipment changes.
Assure quality and repeatability of processes and products.
Engineering bachelor or above, prefer major: automation, mechanical engineering, mathematics, computer Science, information Management, industrial Engineering or related disciplines.
Proven experience as a digital engineer or in a similar role in the manufacturing industry.
- Excellent knowledge of Python programming, with a focus on automation and data analysis.
- Experience with image processing/recognition technologies and their application in a manufacturing setting.
- Strong knowledge in database management and SQL queries.

Required Skills:
Deep understanding and application knowledge of M4.0 hardware platforms and software, including but not limited to embedded systems, sensors, actuators, machine vision systems, robotics technology, and other industrial automation and control systems
(at least 1 or 2 are very professional), and be able to use this knowledge to develop and implement digital solutions.
Programming: 1. Fluent in Python, SQL 2. Familiar with web framework such as Flask and Django 3. Experience with HTML, JavaScript, CSS and Query.
Familiarity with the architecture and technology of the Industrial Internet, such as the Internet of Things (IoT), edge computing, cloud computing, big data, etc., and the ability to consider these factors in hardware selection and design.
Excellent problem-solving skills and ability to think analytically.
Strong verbal and written communication skills, with the ability to explain complex concepts to non-technical team members.
Ability to work collaboratively in a team environment and manage multiple tasks and projects simultaneously.
Use rigorous processes and data to solve problems. Uses a systematic approach to drive to root cause understanding of problems to assure validity of corrective actions.
Good English comprehension in speaking, writing, and reading.
Proactive self-learning is a must in high dynamic working
environment.

Desired Skills:
Strong knowledge and experience in applying Machine Learning (ML), General AI (GenAI), and Large Language Models (LLM) in a manufacturing context.
Proficiency in programming languages: Candidates should be proficient in programming languages such as Python, Java, and C++. This will enable them to develop, test, and troubleshoot digital systems.
Knowledge of data analysis and visualization tools: Candidates should be familiar with tools such as Power BI. This will enable them to analyze and interpret data. and present their findings in a clear and understandable way.
Knowledge of system security and data protection.

Soft Skills:
Strong ownership of achieving plant goal.
Flexibility to adapt to changing environment; be a change agent to help others through change.
Cross-cultural Sensitivity.
Problem-solving abilities: Candidates should possess strong problem-solving skills. They should be able to identify issues with digital systems and develop effective solutions.
Project management skills: Candidates should have experience in managing projects.
This includes planning, organizing, and overseeing projects to ensure they are completed in a timely manner and within budget.
Creativity: Candidates should have the ability to think creatively and come up with innovative solutions to problems.
Continuous learning: The field of digital engineering is constantly evolving, so candidates should be willing to update their skills and knowledge regularly.
Attention to detail: Candidates should have the ability to pay attention to the finer details of a project or task. This is important for identifying and addressing potential issues before they become problems.