Staff~Sr. Staff Machine Learning Engineer (AI Agent) at Coupang

Company Introduction We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we are collectively disrupting the multi-billion-dollar commerce industry from the ground up and establishing an unparalleled reputation for being leading and reliable force in South Korean commerce. We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day. Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. About the Role • Full-Lifecycle LLM Fine-Tuning: Deeply participate in the full-stack algorithm R&D for Coupang's next-generation AI shopping assistant and intelligent customer service products. Lead the full-lifecycle tuning of Large Language Models (LLMs), including Continual Pre-Training (CPT), Supervised Fine-Tuning (SFT), and Reinforcement Learning from Human/AI Feedback (RLHF / Agentic RL). • Large-Scale Agent System Construction: Design and optimize large-scale Agent Orchestration frameworks. Implement tool-calling and sub-agent collaboration mechanisms, empowering the AI assistant to complete the end-to-end shopping loop—spanning pre-sales consultation, price comparison, purchasing, and after-sales service. • Data Flywheel & Feedback Loop: Leverage real user feedback data to build a high signal-to-noise ratio data flywheel and reinforcement learning feedback loop. Continuously drive model iterations to directly boost the user experience and core business metrics. • Generative Multi-Modal Product Discovery: Integrate multi-modal LLM technologies to reinvent traditional search and recommendation pipelines. Build a generative AI-based multi-modal recall, rough-ranking, and fine-ranking system to establish a next-generation, business-goal-oriented intelligent product discovery mechanism. Job Requirements: • Master's degree or above in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. is highly preferred). • Solid practical experience in LLM training and tuning (Pre-training / SFT / RL). Familiar with mainstream deep learning frameworks (e.g., PyTorch) and distributed training technologies. • Deep domain knowledge and a proven track record of implementing solutions in core e-commerce areas, such as intelligent customer service, AI search, AI shopping assistants, or Generative Recommendation. • In-depth understanding and rich project experience in algorithm tuning for Agent architectures, Tool-use, and Multi-Agent Systems. • Practical experience in user personalization modeling, long-text/ultra-long context understanding, and LLM Context Memory management. • Passionate about "reshaping the e-commerce shopping experience with AI." Candidates with high-quality papers published in top-tier AI conferences (e.g., ICML, ACL, AAAI, NeurIPS, ICLR, CVPR) or holding relevant technical patents will be given priority. What We Offer (The Coupang Advantage): • Massive 0-to-1 Business Impact: Lead the creation of a next-generation AI shopping assistant benchmarking against industry leaders (like Rufus). Your models and Agent designs will directly serve tens of millions of global users and fundamentally change how they shop. • Abundant Compute & Cutting-Edge Research: Backed by abundant GPU cluster computing power, the team maintains continuous, heavy investment in frontier research areas such as Agentic Training, Multi-modality, and Generative Recommendation. • Global Vision & Seamless Collaboration: Work alongside top tech talent globally (Seoul, Beijing, Shanghai, MTV, Seattle, etc.). Gain extreme technical depth by being involved in everything from foundational model training to upper-layer Agent systems and the final product experience. • Open & Boundless Culture of Innovation: We reject mechanical, highly-pressured "cog in the machine" cultures. Instead, we encourage a bottom-up geek spirit and technical exploration. We provide a low-friction trial-and-error environment and an inclusive, boundless atmosphere for innovation. Recruitment Process and Others: Recruitment Process • Application Review - Virtual Interviews - Offer • The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances. • Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage. Things to Consider • This job posting may be closed prior to the stated end date for application if all openings are filled. • Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process. • Coupang does not discriminate against disabled applicants or those with veteran status. We are proud to offer equal opportunities for all applicants. Privacy Notice • Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. • [Upgrade to PRO to see link] Document Return Policy • This notification is given pursuant to Article 11 (6) of the Fair Hiring Procedure Act. • A job applicant, who has applied but not been finally selected for a position at Coupang (the “ Company ”), may request the Company to return his/her hiring documents submitted pursuant to the Fair Hiring Procedure Act. However, this will not apply where the hiring documents were submitted via the website of the Company or e-mail, or where the job applicant submitted those documents voluntarily without a request from the Company. In addition, if the hiring documents were destroyed due to a natural disaster or any other reasons not attributable to the Company, such documents will be deemed to have been returned to the job applicant. • A job applicant who wishes to request the return of his/her hiring documents pursuant to the main sentence of paragraph 2 above should fill out a “Request for Return of Hiring Documents” [Annex Form No. 3 in the Enforcement Rule of the Fair Hiring Procedure Act] and submit the request to the Company by email ([Upgrade to PRO to see contact]) In such case, within fourteen (14) days from the date of identifying the receipt of the request, the Company will send the hiring documents to the job applicant’s designated address via registered mail. Please be informed that the job applicant is required to pay the postage on the registered mail. • In preparation for a job applicant’s request for the return of hiring documents pursuant to the main sentence of paragraph 2 above, the Company shall retain the original hiring documents submitted by the job applicant for 180 days from the completion of the recruiting process. If no request is made until the end of this period, all of his/her hiring documents will be destroyed immediately in accordance with the Personal Information Protection Act.