Multimodal LLM Algorithm Engineer Graduate (Global E-Commerce, Knowledge Graph) - 2027 Start (PhD)
Core
Build multimodal content understanding, product understanding, semantic matching, pricing intelligence, and intelligent Agent capabilities for global content-commerce scenarios.
Role type
PhD-level multimodal LLM algorithm engineer (e-commerce)
Builds
Product catalog systems, identical product matching, pricing algorithms, multimodal semantic links, generative search/recommendation, and business-facing Agents.
Domain
Global E-commerce, Knowledge Graph, Multimodal AI
Deliverable
production ML models
Required skills
NLP, Computer Vision, Generative Models (Diffusion, GANs, ControlNet), Multimodal Learning, Large Models, Agents, PyTorch, TensorFlow, Model Training, Model Tuning, Model Deployment
Preferred skills
LLM/VLM, Embedding/SID, RAG, Tool Calling, Agent Planning, Distributed Training, Inference Acceleration, TensorRT, Multimodal Retrieval, AIGC, Video LLMs, Multimodal Reasoning
Technologies
PyTorch, TensorFlow, TensorRT, RAG
Responsibilities
Build global product catalog and content understanding systems; Develop algorithms for identical product matching and cross-lingual aggregation; Build pricing algorithms for price comparison and anomaly detection; Construct multimodal semantic links across video-product relationships; Explore next-generation generative search and recommendation; Design generative algorithms for visual creatives (virtual try-on, scene generation); Explore business-facing Agents (price comparison, product analysis); Own end-to-end algorithm workflow from data construction to deployment.
Seniority
PhD, Research/IC
