Translate client requirements into scalable, maintainable technical solutions. Make informed architectural and technology decisions, balancing business goals, existing systems, technical constraints, budgets, and delivery timelines.
Establish the runtime and governance framework for AI Agents, including execution isolation, permission control, auditability, evaluation, stability, and cost governance.
Work closely with ML engineers to proactively identify and resolve technical challenges , while also contributing directly to the implementation of those improvements. This includes troubleshooting and optimizing machine learning workflows for maximum efficiency and performance, architecting and executing cutting-edge technologies/methodologies for accelerating ML development end-to-end from concept to deployment & maintenance.
Lead the design and development of in-house MES and ERP systems, covering work-in-progress tracking, lot and unit traceability, production planning, inventory, and quality records.
AI Service Enablement: Enable enterprise-wide adoption of AI capabilities by developing reusable APIs, SDKs, templates and shared services that simplify AI integration and accelerate solution delivery across teams, while maintaining AI security and compliance within the organisation.
Develop and apply learning-based planning techniques (e.g. reinforcement and imitation learning) to enhance navigation adaptability and robustness in dynamic environments
Construct multimodal semantic links across video-product, product-product, and video-video relationships to support trend understanding, product mining, AIGC generation, and content-commerce supply optimization.
Design, develop, test, debug, and maintain high-quality software applications, ensuring proper technical documentation and adherence to best practices.
PhD or Master in Computer Science, Computer Vision, Machine Learning, Artificial Intelligence, Applied Mathematics, Electrical Engineering, Robotics, or a closely related technical field.