13 hours ago
Seoul, Korea, SouthStaff+
Responsibilities
- Design and deploy large-scale agentic AI systems with multi-agent orchestration, tool usage, planning, memory, and autonomous reasoning using ReAct and LangGraph.
- Implement post-training reinforcement learning, including RLHF, RLAIF, and reward modeling, to optimize advertiser performance and shopper experience.
- Lead LLM fine-tuning, distillation, and scalable high-throughput, low-latency serving and inference infrastructure.
- Analyze massive advertising datasets and translate discovered patterns into measurable improvements in CTR, CVR, and tROAS.
- Define long-term Ads Growth technical roadmaps and align multinational, cross-functional stakeholders through Korean and English technical design documents.
- Promote rigorous testing, code review, CI/CD, scalable system design, and AI-assisted development workflows using coding agents such as Claude Code.
- Mentor engineers and provide technical leadership across cross-functional organizations.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related technical field.
- 10+ years of professional applied machine learning experience shipping and scaling production ML systems.
- Hands-on experience designing and building multi-agent orchestration, planning, memory, and autonomous reasoning pipelines.
- Proficiency in Python and production-grade software engineering practices, including automated testing, code reviews, CI/CD, and scalable system design.
- Proven ability to set technical direction, establish long-term roadmaps, mentor engineers, and align cross-functional organizations.
- Strong communication skills for collaboration with global teams and multinational stakeholders.
- Preferred: Master’s or Ph.D. in a relevant technical field.
- Preferred: expertise in large-scale digital advertising systems and reward-based post-training reinforcement learning.
- Preferred: experience with LLM fine-tuning, distillation, serving and inference optimization, and end-to-end model training and serving pipelines.
- Preferred: experience with Feature Stores, online/offline evaluation, A/B testing frameworks, massive datasets, and AI coding agents such as Claude Code.
- Preferred: exceptional written communication and ability to document complex architectural tradeoffs for multinational stakeholders.
Benefits
- All interviews are conducted remotely by video, although the process may vary by role and circumstances.
- The posting may close early when all openings are filled.
- Equal opportunity consideration is provided for disabled applicants and applicants with veteran status.
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About Coupang
Coupang builds and operates a South Korea–focused e-commerce marketplace with an end-to-end logistics network (Rocket Delivery), plus food delivery, video streaming, and fintech under brands such as Coupang, Eats, and Play. Revenue comes from first-party retail, third-party marketplace services, advertising, and memberships (Rocket WOW). Founded in 2010, the company is headquartered in Seattle and is publicly listed on the NYSE (CPNG).