Shopee

The Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do.

About the Team:

We are the Customer Service Chatbot team at Shopee Singapore, dedicated to building multilingual, intelligent dialogue systems to serve a wide range of consumers and sellers. We focus on applying cutting-edge AI technologies such as Large Language Models (LLMs), Agents, and Reinforcement Learning (RL) to customer service scenarios, continuously enhancing interaction intelligence and user experience.

We have successfully developed and deployed an efficient LLM-based chatbot system across multiple markets, significantly improving service quality and response efficiency. In the next phase, we will further explore Agentic Workflow–centric system architectures to evolve from traditional Question Answering to intelligent Agents capable of autonomous planning and execution, delivering more natural, intelligent, and efficient conversational experiences.

Join us in shaping the next generation of intelligent customer service chatbots.

Job Description:

You will be involved in or lead the design and development of core algorithms for our chatbot systems, including but not limited to:

• Prompt engineering and response optimization
• Supervised fine-tuning (SFT) and alignment of LLMs
• Multi-turn dialogue context modeling and state tracking
• Agentic dialogue systems driven by workflow execution
• Retrieval-Augmented Generation (RAG) for Question Answering
• Reward model design and strategy optimization via reinforcement learning
• Agent framework design and implementation

You will also work closely with product, business, operations, and engineering teams, participating throughout the full lifecycle—from problem definition and solution design to deployment and iteration—to ensure the effective and continuous improvement of algorithm solutions.

Requirements:

• Bachelor’s degree or above in Computer Science, Artificial Intelligence, Mathematics, or related fields
• Strong foundation in computer science, algorithms, and data structures
• Familiar with the theory and implementation of mainstream models in at least one of the following areas: NLP, LLMs, RL, Agent systems, or Multimodality
• Proficient in at least one programming language (e.g., Python, C++, Go)
• Minimum 4 years of experience with at least one deep learning framework (e.g., PyTorch, TensorFlow)
• Strong English communication skills and ability to work in a cross-functional, international team