SR. Scheduling System Engineer
On-siteTaoyuan, Taiwan, Taiwan or Taichung, Taiwan, Taiwan
Job Summary
Develop, implement, and maintain smart scheduling systems for manufacturing operations while analyzing and optimizing processes to improve productivity. Collaborate with cross-functional teams to determine efficient scheduling solutions and use data-driven insights to successfully implement innovative strategies. Ensure strict adherence to project timelines and deliverables. Leverage AI to analyze problems, structure code development, and visualize results. Requires C#, Python, SQL, and CPLEX expertise with experience in factory scheduling and simulation. Master's degree in Computer Science, Industrial Engineering, or related field preferred.
Required Qualifications
- Master's / Bachelor's Degree in Computer Science, Data Science and Analytics, Industrial Engineering or related field of study
- Programming language capability on C#
- Programming language capability on Python
- Programming language capability on APF Formatter
- Programming language capability on SQL
- Programming language capability on CPLEX
- experience with Snowflake
- experience with GCP
- experience with JS
- Knowledge and experience in factory scheduling
- Knowledge and experience in simulation
- Knowledge and experience in application development
- With growth mindset to be adaptive in a rapidly changing environment
- embrace challenges
- Familiarity with Agile methodology
- Familiarity with Azure
- Familiarity with JIRA
- Familiarity with Git
- Familiarity with Bitbucket
- Familiarity with Confluence
- Using AI to analyze the problem
- Using AI to structuralize the code development & review
- Using AI to validate & visualize the result
Desired Qualifications
- Knowledge and experience in machine learning
- Knowledge and experience in deep learning
- Knowledge and experience in reinforcement learning
- Masters/Bachelor's degree in Industrial Engineering, Operations Research, Computer Science, Computer Engineering, Data Science, other technical fields, or equivalent professional work experience
- Knowledge and experience in simulation
- Knowledge and experience in factory scheduling
- Knowledge and experience in optimization
- Knowledge and experience in machine learning
- Knowledge and experience in reinforcement learning
- Strong FAB operation domain knowledge
- experience in project driving
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