Applicants should have (i) a PhD in Management Science and Engineering, Computer Science, or a related discipline, with a focus on AI/ML theory, algorithms, or applications; (ii) a proven engineering expertise: hands-on experience transforming the theory into scalable production systems, backed by patented innovations; (iii) a proven research record in mathematical AI (e.g., optimization, dynamical systems, graph theory, probabilistic modeling) or adjacent fields with engineering impact; and (iv) fluency in prototyping and software development (e.g., Python, C++, CUDA, or ML frameworks) and interest in open-source collaboration.