Large Recommendation Model Algorithm Engineer Graduate (Global E-Commerce) - 2027 Start (PhD) Singapore Regular PhD Graduates - 2027 Start
Core
Building next-generation recommendation intelligence via unified Foundation Models and event-sequence-driven generative recommendation paradigms.
Role type
PhD-level algorithm engineer (large recommendation models)
Builds
Unified Foundation Models for multi-business recommendation systems (retrieval, ranking, re-ranking)
Domain
E-commerce, Large Language Models (LLMs), Generative AI
Deliverable
production ML models
Required skills
Machine learning, deep learning, information retrieval, Python, PyTorch, LLM integration, multimodal understanding, reinforcement learning
Preferred skills
Large-scale recommendation system development, large-model training, research publications in LLMs/generative recommendation, pre-training/post-training expertise
Technologies
PyTorch, LLMs, VLMs, Foundation Models
Responsibilities
Build and optimize cross-scenario shared Foundation Models; Advance event-sequence-driven generative recommendation paradigm; 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 Graduate, Research & Engineering
