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

What you'll do

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

What they ask for

• Completing or recently completed a Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related discipline.
• Foundation in machine learning and deep learning, plus research or project experience in at least one of: large language models, reinforcement learning, generative models, recommender systems, or information retrieval.
• Proficient 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, especially for live commerce, e-commerce, search, ads, or other large-scale consumer products.
• Relevant experience in generative recommendation, LLMs or multimodal foundation models, recommendation architecture, long-term value modeling, or large-scale training and inference optimization.

Tools

Python, PyTorch, TensorFlow, JAX, LLMs, RL, GPUs

AI focus

Research generative, LLM-powered, and agentic recommendation systems; apply reinforcement learning and optimize long-term value and user experience.