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

About ByteDance

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.

Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.

Responsibilities

• Build global product catalog and content understanding systems, modeling products, videos, images, merchants, and brands with structured and semantic representations.
• 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.
• Build pricing algorithms for price comparison, product pricing, price monitoring, and anomaly detection, supporting subsidy programs, price competitiveness analysis, and supply optimization.
• 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.
• Explore next-generation generative search and recommendation through full-format representation learning and SID modeling across videos, livestreams, products, and queries.
• 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.
• 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.
• Own the end-to-end algorithm workflow, including data construction, model training, evaluation, deployment, badcase analysis, and continuous iteration.

Requirements

• Currently Pursuing a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Strong research or practical experience in NLP, CV, generative models (e.g. Diffusion，GANs，ControlNet) , multimodal learning, large models, or Agents;
• Proficiency in PyTorch / TensorFlow and hands-on experience in model training, tuning, and deployment;

Preferred

• Experience with LLM/VLM, Embedding/SID, RAG, Tool Calling, or Agent Planning is preferred.
• experience with distributed training, mixed precision, inference acceleration, TensorRT, or LLM serving optimization is a plus.
• Experience in multimodal retrieval, product understanding, content understanding, search/recommendation, pricing algorithms, intelligent Agents, or AIGC projects is preferred.
• Passion for frontier AI technologies; familiarity with Video LLMs, Multimodal Reasoning, vision-language alignment, long-video understanding, or generative search/recommendation is a plus.
• Publications, open-source contributions, or strong algorithm competition records are preferred. Strong communication, ownership, and a drive to create real business impact are highly valued.

Application notes

• Applications will be reviewed on a rolling basis, so we encourage you to apply early.
• Please clearly state your availability in your resume (Start date, End date).