Multimodal LLM Algorithm Engineer Graduate (Global E-Commerce, Knowledge Graph) - 2027 Start

About the Team We are part of the Global E-commerce Algorithm team, building multimodal content understanding, product understanding, semantic matching, pricing intelligence, and intelligent Agent capabilities for global content-commerce scenarios. Leveraging our massive-scale video content and global product data, we explore NLP, CV, Multimodal LLMs, Video LLMs, Multimodal Embedding & SID, Multimodal Reasoning, and Agent technologies to power product catalog construction, identical product matching, content-product linking, price comparison, AIGC content generation, and next-generation generative search and recommendation.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities 1. Build global product catalog and content understanding systems, modeling products, videos, images, merchants, and brands with structured and semantic representations. 2. Develop algorithms for identical product matching, product/merchant/brand deduplication, and cross-lingual product aggregation, addressing multimodal matching, real-time aggregation, multi-granularity clustering, and semantic alignment. 3. Build pricing algorithms for price comparison, product pricing, price monitoring, and anomaly detection, supporting subsidy programs, price competitiveness analysis, and supply optimization. 4. 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. 5. Explore next-generation generative search and recommendation through full-format representation learning and SID modeling across videos, livestreams, products, and queries. 6. Design and develop generative algorithms tailored for high engaging, high conversion e-commerce visual creatives, solving challenges in identity-preserving and aesthetic style consistency to produce production-grade intelligent background synthesis，virtual try-on, and localised lifestyle scene generation. 7. Explore business-facing Agents such as price comparison Agents, product analysis Agents, content AIGC Agents, and merchant operation Agents, leveraging RAG, tool calling, planning, reasoning, and automated evaluation. 8. Own the end-to-end algorithm workflow, including data construction, model training, evaluation, deployment, badcase analysis, and continuous iteration.