Large Recommendation Model Algorithm Engineer Graduate (Global E-Commerce) - 2027 Start (PhD)
Core
Building unified Foundation Models for multi-scenario recommendation systems, integrating LLMs, multimodal understanding, and generative capabilities to advance from retrieval to re-ranking.
Role type
PhD-level algorithm engineer (generative recommendation & Foundation Models)
Builds
Unified Foundation Models for e-commerce recommendation pipelines
Domain
E-commerce, Large Language Models, Generative AI
Deliverable
production ML models
Required skills
Python, PyTorch, Machine Learning, Deep Learning, Information Retrieval, LLM integration, Multimodal understanding, Reinforcement Learning, System optimization
Preferred skills
Large-scale recommendation system development, Large-model training, Research publications in LLMs/multimodal/RL, Pre-training and post-training expertise
Technologies
LLMs, VLMs, PyTorch
Responsibilities
Build and optimize cross-scenario shared Foundation Models; Advance event-sequence-driven generative recommendation paradigms; Apply LLM technologies across retrieval, ranking, and re-ranking; Explore LLM/VLM integration with recommenders; Research end-to-end generative recommendation methods.
Seniority
PhD, Research & Engineering