Summary:

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, agents, LLMs, AI, ML, NLP, 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, agents, NLP, LLM, ML and software engineering. Come join us to help create a world class team advancing the AI/NLP/ML/LLM/RL/Knowledge Graph technologies.

The Role/Responsibilities:

• Work on GenAI, self-learning systems to solve complex eCommerce scenarios.
• Develop statistical 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.

What you will bring/ Requirements:

• Overall 10+ years of working in software engineering and AI/ML Engineering.
• 4+ years of demonstrated data science, experience in building large scale foundational models for eCommerce scenarios.
• Expertise in large language model fine-tuning and deployment.
• Deep understanding of AI/ML/Deep-learning and statistical model 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
• Experience in 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