Large Recommendation Model Algorithm Engineer Intern (Global E-Commerce) - 2027 Start (PhD)
Core
Building next-generation unified Foundation Models for multi-scenario e-commerce recommendation systems, integrating LLMs, multimodal understanding, and reinforcement learning to shift from predictive to generative recommendation paradigms.
Role type
PhD intern, large-scale recommendation algorithm engineer (generative AI)
Builds
Unified Foundation Models supporting retrieval, ranking, and re-ranking pipelines for e-commerce
Domain
E-commerce, Generative AI, Large Language Models (LLMs), Multimodal Learning
Deliverable
production ML models
Required skills
Python, PyTorch, Machine Learning theory, Deep Learning, Information Retrieval
Preferred skills
Large-scale recommendation system development, Large-model training, LLM/VLM research, Reinforcement Learning, Pre-training and post-training of Foundation Models
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 stages; Explore integration of LLMs/VLMs with recommendation systems; Research end-to-end generative recommendation and system optimization methods.
Seniority
PhD Intern, Research & Engineering
