Machine Learning Engineer Graduate (E-Commerce Recommendation Mall) - 2027 Start (PhD)

What you'll do

• Research generative recommendation methods, including retrieval and re-ranking, while improving model training and inference efficiency on GPUs.
• Apply LLMs and reinforcement learning to improve recommendation reasoning and address e-commerce challenges such as cold start and user intent understanding.
• Develop agentic recommendation approaches and algorithms for measuring and optimizing long-term value and user experience.

What they ask for

• Completing or recently completed a PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related discipline.
• Solid machine learning and deep learning foundation, with research or project experience in at least one of: LLMs, reinforcement learning, generative models, recommender systems, or information retrieval.
• Proficiency in Python and at least one mainstream deep learning framework.
• Strong problem-solving skills and interest in complex, open-ended research problems.

Nice to have

• Experience in recommendation systems or related large-scale consumer products; generative recommendation, recommendation architecture, or retrieval and ranking systems.
• Experience with LLMs or multimodal foundation models, long-term value modeling, causal inference, user behavior modeling, distributed training, or relevant publications and competition achievements.

Tools

Python, PyTorch, TensorFlow, JAX, GPUs

AI focus

Research generative recommendation, LLM- and reinforcement-learning-enhanced recommendation, self-evolving recommendation agents, and AI-based long-term value and user-experience optimization.