Tech Stack

Description

You will lead the full-lifecycle tuning of Large Language Models (LLMs) for Coupang's next-generation AI shopping assistant and intelligent customer service products. Your work will directly impact tens of millions of users by building generative multi-modal product discovery systems and large-scale agent orchestration frameworks, fundamentally reshaping the e-commerce shopping experience.

Requirements

• Master's or PhD in CS, AI, ML, or related field
• Solid experience in LLM training and tuning (Pre-training/SFT/RL)
• Proficiency in deep learning frameworks (e.g., PyTorch) and distributed training
• Experience in implementing solutions in e-commerce AI (intelligent customer service, AI search, AI shopping assistants, or Generative Recommendation)
• Knowledge of Agent architectures, Tool-use, and Multi-Agent Systems

Responsibilities

• Lead full-lifecycle LLM fine-tuning including CPT, SFT, and RLHF/Agentic RL
• Design and optimize large-scale Agent Orchestration frameworks with tool-calling and sub-agent collaboration
• Build a data flywheel feedback loop using real user feedback to drive model iterations
• Integrate multi-modal LLM technologies to reinvent search and recommendation pipelines
• Develop generative AI-based multi-modal recall, ranking, and product discovery systems