Key Responsibilities:

1. Define the overall technical roadmap for the company’s AI-driven supply chain intelligent decision-making system.

2. Lead the development of core algorithms, including supply chain risk prediction, production scheduling optimization, logistics delay alerts, and inventory anomaly detection.

3. Apply advanced methods such as machine learning, mathematical optimization, and control theory to product design and development.

4. Design the company’s core algorithm and system architecture, ensuring smooth transition from R&D prototypes to production-ready solutions.

5. Manage and mentor the technical team, coordinating work across algorithms, data processing, and engineering development.

6. Participate in the technical design, system deployment, and ongoing support for key client projects.

Minimum Entry Requirements:

1. PhD in Control Science and Engineering, Automation, Data and Systems Engineering, Operations Research/Optimization, Artificial Intelligence, Computer Science, or a related field.

2. Research or practical experience in machine learning, mathematical optimization, control theory, and complex scheduling systems.

3. Proficiency in integer programming, mixed-integer programming, decomposition algorithms, and machine learning-assisted optimization techniques.

4. Practical experience in supply chain scheduling, semiconductor manufacturing scheduling, job-shop scheduling, or other NP-hard optimization problems.

5. Ability to translate advanced algorithms into enterprise-level systems or commercial products.

6. Capability in leading technical teams, designing system architectures, and collaborating effectively across departments.