Staff Machine Learning Engineer

Job Description At Coupang, we invest in providing the best product experience for our customers. The AI and Knowledge Engineering team’s mission is to provide the best possible technical solution to achieve the optimal experience for our customers. We innovate and advance the space of Knowledge Graphs, AI agents, LLMs, AIGC, ML, NLP, CV and multi-modal models. We are looking for engineers who want to work on cutting edge technology, that is the intersection of Semantic knowledge bases, AI agents, NLP, LLM, AIGC, ML and software engineering. Come join us to help create a world class team advancing the AI/NLP/AIGC/ML/LLM/RL/Knowledge Graph technologies.  Responsibilities:Work on GenAI, AI agents' systems to solve complex eCommerce scenarios. Develop large language and vision understanding/generation models for predictive and compound AI Models Train foundational models that can help with building learning systems. Define process and experiments for an E2E foundation model. Build E2E AI pipelines for storing/servicing foundational models. Mentor and guide team members on frameworks, methodologies related to data lakes, data normalization, dimension reduction, visualization, statistical models. Ensure Model training is security, compliance aware. Collaborate with cross-team members to understand the requirements ensuring the foundational models; knowledge captured aligns with the company’s overall AI strategy.  Basic Qualifications: 5+ years of demonstrated data science, experience in building large scale foundational models for eCommerce scenarios. Expertise in large language model post-training and deployment. Deep understanding of AI/LLM/AIGC/ML architecture. Strong statistical/mathematical background in defining metrics, learning functions, and result analysis. Significant experience in SQL, Python, PySpark, Scala and R Proficiency in PyTorch/TensorFlow, Spark, BigQuery Proficiency in AI coding Cursor/Windsurf/Claude Code/Codex. Experience creating complex data visualization tools, frameworks, and techniques. Experience in dimension reduction in big data. Proficient in cloud analytical stacks [ Lakes, warehouse, ETL pipelines] Experience with inference platforms in AWS, Azure, and other open-source platforms. Are result-oriented, with a bias towards customer obsession, flexibility, and impact. Strong written and verbal communication and teamwork skills Passion for Large language models, NLP, and Machine Learning at scale Education: B.S, M.S in Computer science or Mathematics, or related field