Job Description
Team Introduction
The future of e-commerce customer service is intelligent, efficient, and AI-driven. Our team is dedicated to replacing traditional human-agent customer service with an advanced AI-powered conversational system that provides instant, intelligent, and seamless support for global e-commerce platform. By leveraging Large Language Models (LLMs) and NLP, we are building an AI customer service system that can understand user queries, resolve disputes, guide transactions, and enhance the overall shopping experience without the need for human intervention.
Our cutting-edge AI is designed to handle complex customer interactions, including answering product inquiries, resolving order issues, processing refunds, and assisting sellers with operational tasks. Through LLM post-training, we ensure that our AI assistant is continuously learning and improving, providing more accurate, context-aware, and human-like interactions.
By joining us, you will be at the forefront of transforming customer service in e-commerce, helping build an AI system that understands, adapts, and provides intelligent solutions—all while reducing costs and improving efficiency for merchants and the platform.
We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.
Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Responsibilities
- Develop AI Customer Support Systems: Build and optimize AI-driven customer service models capable of handling high-volume, complex user inquiries while ensuring high response accuracy and reliability.
- Enhance LLM-Based Customer Interaction Models: Implement LLM post-training strategies to improve customer support interactions, reducing errors, hallucinations, and irrelevant responses.
- Create Automated Dispute Resolution & Policy-Adaptive AI: Develop intelligent models capable of handling disputes, verifying transaction details, and ensuring platform compliance in automated responses.
- Develop Multilingual Support & Translation Models: Enhance the platform’s AI translation capabilities for real-time multilingual customer service interactions, ensuring smooth cross-language communication.
- Refine Response Evaluation Metrics: Define and implement quality evaluation metrics for AI-generated responses to track customer satisfaction and improve conversational AI quality through A/B testing and iterative optimization.
- Enable AI-Seller Collaboration: Build AI-powered seller assistance tools to help merchants quickly respond to customer inquiries, manage store operations, and resolve disputes efficiently.
- Optimize Large-Scale Model Deployment: Work on model compression, inference optimization, and edge AI deployment to ensure real-time, high-quality customer service experiences at scale.
