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.
PhD or Master in Computer Science, Computer Vision, Machine Learning, Artificial Intelligence, Applied Mathematics, Electrical Engineering, Robotics, or a closely related technical field.
Collaborate with data scientists to improve feature selection, feature engineering, and enable end-to-end AI workflows from model training to deployment and monitoring.
Demonstrable payment processing and clearing knowledge especially data mapping and modelling to support triaging issues raised in development and production
Work closely with the SPEED architect, quantitative researchers, and the business to provide high ROI solutions that are aligned with both the business and the platform strategy.
Partner closely with IC design teams to ensure to deliver comprehensive technical specifications, rigorous benchmark reports, and high-value patent proposals.
Make integration effortless: Create reusable frameworks, SDKs, and configuration patterns so new connectors and integrations can be built quickly and maintained reliably.
Infrastructure & Performance Optimization: Manage and optimize GPU/accelerator infrastructure (on cloud platforms like AWS, Azure, GCP or on-prem NVIDIA clusters) to support high-performance model training and inference. Drive token efficiency, latency reduction, and cost optimization in AI pipelines (through techniques like model quantization, batching, and caching).