Pursue business opportunities with electronics and electrical appliance brands, manufacturers, energy storage and industrial equipment companies, and recycling traders.
Pursue business with electronics and electrical appliance brands, manufacturers, energy storage and industrial equipment companies, and recycling traders.
Team Introduction: The Data-Global E-Commerce team serves as the core technological engine for ByteDance's Global E-commerce. We specialize in pioneering algorithmic and big data innovations within the E-commerce sector, driven by our mission: "To make a beautiful life readily accessible and to help unique, high-quality products reach a global market." Our work involves: Developing advanced recommendation and search algorithms to help users efficiently discover products that match their interests. Leveraging cutting-edge risk control and platform governance technologies to ensure a secure shopping environment for all users. Constructing a comprehensive product knowledge graph and intelligent customer service systems to elevate the intelligence of every stage of the transaction process. Integrating machine learning with operations research algorithms to continuously optimize supply chain and logistics efficiency, thereby reducing operational costs. Providing merchants with intelligent business tools that empower them to enhance their operational efficiency and customer service experience. By joining us, you will collaborate with world-class product and technology teams, leveraging ByteDance's extensive traffic and data ecosystem to drive the deep integration and application of technology across various e-commerce scenarios.
As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. The Research Fellow / Research Engineer will support a research project focused on the development of data-driven modelling, optimisation, and decision-support tools for food and nutrition systems. The successful candidate will work closely with the Principal Investigator on research activities involving data analytics, computational modelling, machine learning, and optimisation. The role offers opportunities to contribute to research publications, technical development, and industry-relevant project outcomes in the areas of food sustainability, nutrition, and supply chain decision-making.
Excellent programming abilities in leading or participating in key projects related to Search, Advertising, Recommendation systems, or Large Language Models (LLMs).
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 in Computer Science, Artificial Intelligence, Machine Learning, or related fields preferred or strong industry experience in similar fields, ideally with familiarity with Asia-Pacific/Singapore research resources.
ML Pipeline Contribution: Package models in Docker; contribute to CI/CD scripts under guidance; run inference tests and support deployment validation in product development environments.
Partner closely with IC design teams to ensure to deliver comprehensive technical specifications, rigorous benchmark reports, and high-value patent proposals.
Participate in building a large-scale graph storage and graph learning platform to improve relationship building and governance within the e-commerce community.
Production operations— When something breaks in front of real users, you're the one who fixes it. Then you bake the fix into the platform so the next FDE doesn't hit it.
Maintain an updated broad product, competitor and disease knowledge, pharmacy and therapeutic process knowledge in therapeutic area to build professional customer relationships and support sound clinical discussions.
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).
Collaborate closely with IT operations and DevOps teams to ensure the smooth integration of infrastructure platforms with other applications and processes.
PhD in Computer Science, Artificial Intelligence, Machine Learning, or related fields preferred or strong industry experience in similar fields, ideally with familiarity with Asia-Pacific/Singapore research resources.
