Machine Learning Engineer Graduate

About the Role

We are seeking a graduate Machine Learning Engineer to join our E-commerce Recommendation Team. The role focuses on advancing generative, LLM-powered, and agentic recommender systems while developing models that optimize long-term value and user experience in e-commerce.

Responsibilities

• Generative Recommendation Research: Drive the evolution of recommender systems from discriminative to generative paradigms; explore frontier directions such as generative retrieval and generative re-ranking/blending; continuously improve personalization capabilities while deeply optimizing training and inference efficiency on GPUs.
• LLM for Recommendation Research: Leverage Large Language Models (LLMs), Reinforcement Learning (RL), and related techniques to enhance semantic understanding and reasoning in recommender systems, addressing core business challenges like cold start problems, long-tail item distribution, and user intent understanding.
• Agentic Recommendation Research: Explore the construction of self-evolving agents; leverage agents to continuously optimize recommender systems toward agentic architectures capable of keenly perceiving user context for real-time, personalized decisions.
• Long-Term Value and User Experience Modeling: Replace traditional heuristic rule-based systems with LLM and agent capabilities; build next-generation algorithms for measuring and optimizing long-term value (LTV) to enable sustainable platform growth.